美赛历年赛题

2019美赛数学建模题目摘要：1.2019 美赛数学建模题目概述2.题目分类与解析3.题目难度与挑战4.中国高校表现与启示正文：【2019 美赛数学建模题目概述】美国大学生数学建模竞赛（MCM/ICM）是全球范围内最具影响力的数学建模竞赛，每年有来自世界各地的数千所高校参赛。

2019 年美赛数学建模题目共有6 道题目，涵盖了多个领域，旨在考验参赛选手的数学应用、分析与解决问题的能力。

【题目分类与解析】2019 年美赛数学建模题目分为A、B、C、D、E、F 六道题目，具体分类如下：A 题：疾病传播的动力学模型B 题：飞机设计的优化问题C 题：城市交通网络的优化设计D 题：环境污染物在河流中的传播与治理E 题：无人机编队的路径规划问题F 题：社交网络的社区检测问题每道题目都具有一定的挑战性，要求参赛选手对相关领域的知识有深入了解，并具备较强的数学建模能力。

【题目难度与挑战】2019 年美赛数学建模题目难度适中，但涉及的领域较广，对参赛选手提出了较高的要求。

在解题过程中，选手需要充分运用自己所学的专业知识，对题目进行深入分析，找到问题的关键所在，并提出创新性的解决方案。

因此，参赛选手在比赛中面临的挑战主要来自于对题目的理解和解决问题的能力。

【中国高校表现与启示】在2019 年美赛数学建模竞赛中，中国高校表现优异，获得了多个奖项。

这得益于我国高校对数学建模教育的重视，以及学生在老师的指导下，通过参加训练、模拟赛等形式，提高了自己的数学建模能力。

对于今后参赛的高校和学生，可以从以下几个方面进行准备：1.提高专业素养，熟练掌握相关领域的知识；2.加强数学建模培训，提高解决实际问题的能力；3.注重团队合作，发挥团队成员的优势，共同完成题目。

A题设计一个交通环岛在许多城市和社区都建立有交通环岛，既有多条行车道的大型环岛（例如巴黎的凯旋门和曼谷的胜利纪念碑路口），又有一至两条行车道的小型环岛。

有些环岛在进入口设有“停车”标志或者让行标志，其目的是给已驶入环岛的车辆提供行车优先权；而在一些环岛的进入口的逆向一侧设立的让行标志是为了向即将驶入环岛的车辆提供行车优先权；还有一些环岛会在入口处设立交通灯（红灯会禁止车辆右转）；也可能会有其他的设计方案。

这一设计的目的在于利用一个模型来决定如何最优地控制环岛内部，周围以及外部的交通流。

该设计的目的在于可利用模型做出最佳的方案选择以及分析影响选择的众多因素。

解决方案中需要包括一个不超过两页纸，双倍行距打印的技术摘要，它可以指导交通工程师利用你们模型对任何特殊的环岛进行适当的流量控制。

该模型可以总结出在何种情况之下运用哪一种交通控制法为最优。

当考虑使用红绿灯的时候，给出一个绿灯的时长的控制方法（根据每日具体时间以及其他因素进行协调）。

找一些特殊案例，展示你的模型的实用性。

B题能源和手机这个问题涉及到手机革命的能源问题。

手机使用率迅速增加，许多人使用手机并放弃了固定电话。

这方面的电能使用会带来什么后果？每个手机都配备了电池和充电器。

要求1考虑现在的美国，人口约为3亿，从现有数据估计美国有H个家庭，每个家庭有M个成员，以前是使用固定电话的。

现在，假设所有的座机被手机取代，也就是说每个家庭成员都有一部手机。

建立当前美国在手机使用的过渡和稳定两个阶段用电改变的模型，分析应该考虑到对移动电话充电的需要，同时移动电话不能像固定电话那样长期使用也是一个现实问题（比如说移动电话可能会丢失或者损坏）要求2考虑“伪美国”--一个约3亿人口，跟当前美国具有相同的经济状况的国家。

然而，这个新兴国家既没有固定电话也没有移动电话，从能源角度看，为这个国家提供电话服务的最佳方式是什么？当然，手机有很多固定电话所不具有的用途和社会影响。

2017年美赛题目2017年美赛（MCM/ICM）共有6个题目，分别是：1. Problem A: The Art of Archery.这个问题涉及到弓箭射击的技术和策略。

要求团队通过建立数学模型，分析射击的精度和效率，并给出最佳的射击策略。

2. Problem B: The Search for the Lost Dutchman's Gold Mine.这个问题要求团队通过模拟和优化算法，规划一次寻找失落的荷兰人金矿的探险。

团队需要考虑资源分配、路线选择和风险评估等因素。

3. Problem C: The Great American Potato Chip Factory.这个问题要求团队分析和优化一个薯片工厂的生产过程。

团队需要考虑原材料采购、生产调度和产品分配等方面，以提高工厂的效率和利润。

4. Problem D: The Mathematics of Music.这个问题要求团队通过数学模型和计算方法，分析和优化音乐的和声和旋律结构。

团队需要考虑音乐的音高、音长和节奏等因素，并给出最佳的音乐创作建议。

5. Problem E: The Internet of Things.这个问题要求团队分析和优化物联网中的传感器网络。

团队需要考虑传感器的部署、数据传输和能源管理等问题，以提高网络的覆盖范围和性能。

6. Problem F: The Impacts of Tourism.这个问题要求团队通过建立模型，分析旅游业对一个地区的经济、环境和社会影响。

团队需要考虑游客数量、旅游收入和环境保护等因素，并给出合理的政策建议。

以上是2017年美赛的题目概述，每个题目都涉及不同的领域和问题，需要团队综合运用数学建模、数据分析和优化方法来解决。

2024年美赛竞赛赛题解析（中英文版）英文文档：Title: Analysis of the 2024 American Mathematics Competition (AMC) QuestionsThe American Mathematics Competition (AMC) is an annual mathematics examination for high school students in the United States.The 2024 AMC questions are designed to test students" mathematical knowledge, problem-solving skills, and creativity.In this article, we will analyze the key features and trends of the 2024 AMC questions.Firstly, the 2024 AMC questions cover a wide range of mathematical topics, including algebra, geometry, probability, and calculus.These topics are essential components of a comprehensive mathematics education.The questions are designed to assess students" understanding of these topics and their ability to apply mathematical concepts to solve problems.Secondly, the 2024 AMC questions require students to think critically and logically.Many questions are word problems that require students to interpret mathematical information, identify relevant equations or theorems, and develop a plan to solve the problem.The ability to communicate mathematical ideas clearly and effectively is alsoan important aspect of the examination.Thirdly, the 2024 AMC questions emphasize problem-solving skills.Students are required to use various strategies, such as substitution, elimination, and iteration, to find solutions.The examination also tests students" ability to estimate solutions and determine the reasonableness of their answers.Fourthly, the 2024 AMC questions encourage students to think creatively and explore mathematical concepts beyond traditional problem-solving methods.Some questions may have multiple solutions or require students to develop their own original solutions.This encourages students to think outside the box and explore the boundaries of mathematical knowledge.In conclusion, the 2024 American Mathematics Competition (AMC) questions are designed to assess students" mathematical knowledge, problem-solving skills, and creativity.The questions cover a wide range of topics and require students to think critically, logically, and creatively.By participating in the AMC, students can improve their mathematical abilities and expand their horizons in the field of mathematics.中文文档：标题：2024年美国数学竞赛（AMC）题目解析美国数学竞赛（AMC）是一项年度数学考试，面向美国高中学生。

2009 Contest ProblemsMCM PROBLEMSPROBLEM A: Designing a Traffic CircleMany cities and communities have traffic circles—from large ones with many lanes in the circle (such as at the Arc de Triomphe in Paris and the Victory Monument in Bangkok) to small ones with one or two lanes in the circle. Some of these traffic circles position a stop sign or a yield sign on every incoming road that gives priority to traffic already in the circle; some position a yield sign in the circle at each incoming road to give priority to incoming traffic; and some position a traffic light on each incoming road (with no right turn allowed on a red light). Other designs may also be possible.The goal of this problem is to use a model to determine how best to control traffic flow in, around, and out of a circle. State clearly the objective(s) you use in your model for making the optimal choice as well as the factors that affect this choice. Include a Technical Summary of not more than two double-spaced pages that explains to a Traffic Engineer how to use your model to help choose the appropriate flow-control method for any specific traffic circle. That is, summarize the conditions under which each type of traffic-control method should be used. When traffic lights are recommended, explain a method for determining how many seconds each light should remain green (which may vary according to the time of day and other factors). Illustrate how your model works with specific examples.MCM2009问题A : 设计一个交通环岛在许多城市和社区都建立有交通环岛，既有多条行车道的大型环岛（例如巴黎的凯旋门和曼谷的胜利纪念碑路口），又有一至两条行车道的小型环岛。

美赛习题答案美赛习题答案在数学建模领域，美国大学生数学建模竞赛（MCM）是一项备受关注的赛事。

每年，来自全球各地的大学生们都会参与其中，挑战各种实际问题并提出解决方案。

这项竞赛不仅考察了参赛者的数学水平，更重要的是培养了他们的团队合作和创新思维能力。

本文将探讨一些典型的美赛习题，并给出相应的解答。

第一题是关于城市交通流量的问题。

题目给出了一个城市的道路网络图，要求我们计算出每条道路的平均交通量。

首先，我们可以通过收集实际交通数据来估计每条道路上的车辆数量。

然后，根据道路的长度和车辆数量，我们可以计算出每条道路的平均交通量。

最后，将结果绘制成热力图，可以清晰地显示出城市交通的拥堵情况。

第二题是关于电力系统的问题。

题目给出了一个电力系统的拓扑结构图，要求我们设计一种最优的电力传输方案，以最大化系统的可靠性和效率。

首先，我们可以使用图论的方法对电力系统进行建模，并计算出各个节点之间的电力传输路径。

然后，根据节点之间的电力传输损耗和供电能力，我们可以通过线性规划等数学方法得到最优的电力传输方案。

最后，我们可以通过模拟实验来验证我们的方案，并对其进行优化。

第三题是关于航空公司的问题。

题目给出了一家航空公司的航班数据，要求我们设计一种最优的航班调度方案，以最大化公司的利润和乘客满意度。

首先，我们可以使用图论的方法对航班网络进行建模，并计算出各个航班之间的飞行时间和成本。

然后，根据乘客的需求和航班的运营成本，我们可以通过线性规划等数学方法得到最优的航班调度方案。

最后，我们可以通过模拟实验来验证我们的方案，并对其进行优化。

以上只是美赛习题中的几个例子，实际上还有许多其他有趣的问题，涉及到经济、环境、医疗等领域。

解决这些问题需要我们具备扎实的数学基础和创新的思维能力。

在解题过程中，我们需要灵活运用数学模型和工具，结合实际情况进行分析和判断。

同时，团队合作也是解决问题的关键，每个人都应发挥自己的优势，共同努力达到最佳的解决方案。

2024美赛题目解析今天咱们一起来看看2024年美赛的题目。

美赛可是一个很有挑战性也很有意思的竞赛，每年的题目都能让大家开动脑筋，想出各种奇妙的解法。

下面咱们就一道一道来分析分析。

题目A：“最佳觅食策略”题目内容和背景。

想象一下，动物们在野外要找吃的，这可不是一件简单的事儿。

它们得考虑好多因素，比如食物的分布情况、找食物要花多少精力、周围有没有危险等等。

就好比一只小松鼠，它要在树林里找坚果，有的地方坚果多，有的地方少，它还得小心别被老鹰抓走，这就是这个题目的背景啦。

解题思路。

要解决这个问题，咱们可以先确定一些关键因素。

比如说食物的能量值，就像一颗大坚果比一颗小坚果能量多；还有获取食物的难度，像藏在树洞里的坚果就比地上的难拿到。

然后呢，咱们可以建立一个模型，来计算动物在不同情况下的觅食收益。

比如说，小松鼠如果花5分钟在地上找到一颗小坚果，获得10单位的能量；花15分钟在树洞里找到一颗大坚果，能获得30单位的能量。

通过比较这些不同情况，就能找到最佳的觅食策略啦。

实际应用案例。

这个问题在现实生活中也有很多应用哦。

比如农民伯伯要规划种植哪些农作物，他们得考虑每种农作物的产量（就像食物的能量值），还有种植和管理的难度（获取食物的难度）。

这样才能决定怎么安排土地，获得最大的收益。

题目B：“水资源可持续性规划”题目内容和背景。

水可是咱们生活中必不可少的东西，但是现在水资源越来越紧张啦。

很多地方都面临着缺水的问题，就像有些干旱地区，人们连喝水都成问题。

所以咱们得想想办法，怎么合理地规划和利用水资源，让它能够可持续发展。

解题思路。

咱们得了解当地的水资源状况，包括有多少河流、湖泊，降雨量是多少等等。

然后根据不同的用水需求，像居民生活用水、农业灌溉用水、工业生产用水等，制定合理的分配方案。

比如说，在干旱地区，可以推广节水灌溉技术，像滴灌，这样就能用更少的水灌溉更多的庄稼。

还可以建立污水处理系统，把用过的水经过处理后再利用。

2024数学建模美赛c题
2024年美国大学生数学建模竞赛C题是关于网球中的动量的问题。

该题目
要求参赛者探讨网球中的动量，以及动量如何影响网球的弹跳和飞行。

该题目提供了一些数据，包括不同速度和重量的网球的弹跳高度和飞行距离。

参赛者需要使用这些数据来建立数学模型，以解释动量如何影响网球的弹跳和飞行。

在建立模型的过程中，可以使用不同的数学工具和软件，例如Python、Matlab、Excel等。

在解释数据时，可以使用回归分析、统计分析、机器学习等方法。

最后，参赛者需要将建立的模型应用于实际情境中，例如在网球比赛中如何使用动量来提高击球效果。

同时，还需要回答题目中提出的问题，例如“为什么动量对网球的弹跳和飞行有影响？”、“如何利用动量来提高网球比赛的表现？”等。

总之，2024年美国大学生数学建模竞赛C题是一个有趣且具有挑战性的问题，需要参赛者具备扎实的数学基础和良好的数据分析能力。

2003 MCM ProblemsPROBLEM A: The Stunt PersonAn exciting action scene in a movie is going to be filmed, and you are the stunt coordinator! A stunt person on a motorcycle will jump over an elephant and land in a pile of cardboard boxes to cushion their fall. You need to protect the stunt person, and also use relatively few cardboard boxes (lower cost, not seen by camera, etc.).Your job is to:•determine what size boxes to use•determine how many boxes to use•determine how the boxes will be stacked•determine if any modifications to the boxes would help•generalize to different combined weights (stunt person & motorcycle) and different jump heightsNote that, in "Tomorrow Never Dies", the James Bond character on a motorcycle jumps over a helicopter.PROBLEM B: Gamma Knife Treatment PlanningStereotactic radiosurgery delivers a single high dose of ionizing radiation to a radiographically well-defined, small intracranial 3D brain tumor without delivering any significant fraction of the prescribed dose to the surrounding brain tissue. Three modalities are commonly used in this area; they are the gamma knife unit, heavy charged particle beams, and external high-energy photon beams from linear accelerators.The gamma knife unit delivers a single high dose of ionizing radiation emanating from 201 cobalt-60 unit sources through a heavy helmet. All 201 beams simultaneously intersect at the isocenter, resulting in a spherical (approximately) dose distribution at the effective dose levels. Irradiating the isocenter to deliver dose is termed a “shot.” Shots can be represented as different spheres. Four interchangeable outer collimator helmets with beam channel diameters of 4, 8, 14, and 18 mm are available for irradiating different size volumes. For a target volume larger than one shot, multiple shots can be used to cover the entire target. In practice, most target volumes are treated with 1 to 15 shots. The target volume is a bounded, three-dimensional digital image that usually consists of millions of points.The goal of radiosurgery is to deplete tumor cells while preserving normal structures.Since there are physical limitations and biological uncertainties involved in this therapy process, a treatment plan needs to account for all those limitations and uncertainties. In general, an optimal treatment plan is designed to meet the following requirements.1.Minimize the dose gradient across the target volume.2.Match specified isodose contours to the target volumes.3.Match specified dose-volume constraints of the target and critical organ.4.Minimize the integral dose to the entire volume of normal tissues or organs.5.Constrain dose to specified normal tissue points below tolerance doses.6.Minimize the maximum dose to critical volumes.In gamma unit treatment planning, we have the following constraints:1.Prohibit shots from protruding outside the target.2.Prohibit shots from overlapping (to avoid hot spots).3.Cover the target volume with effective dosage as much as possible. But at least90% of the target volume must be covered by shots.e as few shots as possible.Your tasks are to formulate the optimal treatment planning for a gamma knife unit as a sphere-packing problem, and propose an algorithm to find a solution. While designing your algorithm, you must keep in mind that your algorithm must be reasonably efficient.2002 Contest ProblemsProblem AAuthors: Tjalling YpmaTitle: Wind and WatersprayAn ornamental fountain in a large open plaza surrounded by buildings squirts water high into the air. On gusty days, the wind blows spray from the fountain onto passersby. The water-flow from the fountain is controlled by a mechanism linked to an anemometer (which measures wind speed and direction) located on top of an adjacent building. The objective of this control is to provide passersby with an acceptable balance between an attractive spectacle and a soaking: The harder the wind blows, the lower the water volume and height to which the water is squirted, hence the less spray falls outside the pool area.Your task is to devise an algorithm which uses data provided by the anemometer to adjust the water-flow from the fountain as the wind conditions change.Problem BAuthors: Bill Fox and Rich WestTitle: Airline OverbookingYou're all packed and ready to go on a trip to visit your best friend in New York City. After you check in at the ticket counter, the airline clerk announces that your flight has been overbooked. Passengers need to check in immediately to determine if they still have a seat.Historically, airlines know that only a certain percentage of passengers who have made reservations on a particular flight will actually take that flight. Consequently, most airlines overbook-that is, they take more reservations than the capacity of the aircraft. Occasionally, more passengers will want to take a flight than the capacity of the plane leading to one or more passengers being bumped and thus unable to take the flight for which they had reservations.Airlines deal with bumped passengers in various ways. Some are given nothing, some are booked on later flights on other airlines, and some are given some kind of cash or airline ticket incentive.Consider the overbooking issue in light of the current situation:Less flights by airlines from point A to point BHeightened security at and around airportsPassengers' fearLoss of billions of dollars in revenue by airlines to dateBuild a mathematical model that examines the effects that different overbooking schemes have on the revenue received by an airline company in order to find an optimal overbooking strategy, i.e., the number of people by which an airline should overbook a particular flight so that the company's revenue is maximized. Insure that your model reflects the issues above, and consider alternatives for handling "bumped" passengers. Additionally, write a short memorandum to the airline's CEO summarizing your findings and analysis.MCM2000Problem A Air traffic ControlTo improve safety and reduce air traffic controller workload, the Federal Aviation Agency (FAA) is considering adding software to the air traffic control system that would automatically detect potential aircraft flight path conflicts and alert the controller. To that end, an analyst at the FAA r traffic control system that would automatically detect potential aircraft flight path conflicts and alert the controller. To that end, an analyst at the FAA has posed the following problemsRequirement A: Given two airplanes flying in space, when should the air traffic controller ld the air traffic controller consider the objects to be too close and to require intervention?Requirement B: An airspace sector is the section of three-dimensional airspace that one air traffic controller controls. Given any airspace sector, how we measure how complex it is from an air traffic workload perspective? To what extent is complexity determined by the number of we measure how complex it is from an air traffic workload perspective? To what extent is complexity determined by the number of aircraft simultaneously passing through that sector (1) at any one instant? (2) During any given interval of time? (3) During particular time of day? How does the number of potential conflicts arising during those periods affect complexity?Does the presence of additional software tools to automatically predict conflicts and alert the controller reduce or add to this complexity?In addition to the guidelines for your report, write a summary (no more than two pages) that the FAA analyst can present to Jane Garvey, the FAA Administrator, to defend your conclusionsProblem B Radio Channel AssignmentsWe seek to model the assignment of radio channels to a symmetric network of transmitter locations over a large planar area, so as to avoid interference. One basic approach is to partition the region into regular hexagons in a grid (honeycomb-style), as shown in Figure 1, where a transmitter is located at the center of each hexagon.An interval of the frequency spectrum is to be allotted for transmitter frequencies. The interval will be divided into regularly spaced channels, which we represent by integers 1, 2, 3, ... . Each transmitter will be assigned one positive integer channel. The same channel can be used at many locations, provided that interference from nearby transmitters is avoided. Our goal is to minimize the width of the interval in the frequency spectrum that is needed to assign channels subject to some constraints. This is achieved with the concept of a span. The span is the minimum, over all assignments satisfying the constraints, of the largest channel used at any location. It is not required that every channel smaller than the span be used in an assignment that attains the span.Let s be the length of a side of one of the hexagons. We concentrate on the case that there are two levels of interferenceRequirement A: There are several constraints on frequency assignments. First, no two transmitters within distance of each other can be given the same channel. Second, due to spectral spreading, transmitters within distance 2s of each other must not be given the same or adjacent channels: Their channels must differ by at least 2. Under these constraints, what can we say about the span in,Requirement B: Repeat Requirement A, assuming the grid in the example spreads arbitrarily far in all directions.Requirement C: Repeat Requirements A and B, except assume now more generally that channels for transmitters within distance differ by at least some given integer k, while those at distance at most must still differ by at least one. What can we say about the span and about efficient strategies for designing assignments, as a function of k?Requirement D: Consider generalizations of the problem, such as several levels of interference or irregular transmitter placements. What other factors may be important to consider?Requirement E: Write an article (no more than 2 pages) for the local newspaper explaining your findingsMCM2000问题A 空间交通管制为加强安全并减少空中交通指挥员的工作量，联邦航空局(FAA)考虑对空中交通管制系统添加软件，以便自动探测飞行器飞行路线可能的冲突，并提醒指挥员。

1985 年美国大学生数学建模竞赛MCM 试题1985年MCM:动物种群选择合适的鱼类和哺乳动物数据准确模型。

模型动物的自然表达人口水平与环境相互作用的不同群体的环境的重要参数,然后调整账户获取表单模型符合实际的动物提取的方法。

包括任何食物或限制以外的空间限制,得到数据的支持。

考虑所涉及的各种数量的价值,收获数量和人口规模本身,为了设计一个数字量代表的整体价值收获。

找到一个收集政策的人口规模和时间优化的价值收获在很长一段时间。

检查政策优化价值在现实的环境条件。

1985年MCM B:战略储备管理钴、不产生在美国,许多行业至关重要。

(国防占17%的钴生产。

1979年)钴大部分来自非洲中部,一个政治上不稳定的地区。

1946年的战略和关键材料储备法案需要钴储备,将美国政府通过一项为期三年的战争。

建立了库存在1950年代,出售大部分在1970年代初,然后决定在1970年代末建立起来,与8540万磅。

大约一半的库存目标的储备已经在1982年收购了。

建立一个数学模型来管理储备的战略金属钴。

你需要考虑这样的问题:库存应该有多大?以什么速度应该被收购?一个合理的代价是什么金属?你也要考虑这样的问题:什么时候库存应该画下来吗?以什么速度应该是画下来吗?在金属价格是合理出售什么?它应该如何分配?有用的信息在钴政府计划在2500万年需要2500万磅的钴。

美国大约有1亿磅的钴矿床。

生产变得经济可行当价格达到22美元/磅(如发生在1981年)。

要花四年滚动操作,和thsn六百万英镑每年可以生产。

1980年,120万磅的钴回收,总消费的7%。

1986 年美国大学生数学建模竞赛MCM 试题1986年MCM A:水文数据下表给出了Z的水深度尺表面点的直角坐标X,Y在码(14数据点表省略)。

深度测量在退潮。

你的船有一个五英尺的草案。

你应该避免什么地区内的矩形(75200)X(-50、150)?1986年MCM B:Emergency-Facilities位置迄今为止,力拓的乡牧场没有自己的应急设施。

美赛金融题目美国大学生数学建模竞赛分为两种类型：MCM（Mathematical Contest In Modeling）和ICM（Interdisciplinary Contest In Modeling)两种类型竞赛采用统一标准进行，竞赛题目出来之后，参数队伍通过美赛官网进行选题，一共分为6种题型。

MCM是包括A、B、C三道题目：-- A题是指连续型（continuous），具体可以理解为是连续函数建立一类模型。

常用方法是微分方程，并多为“数值分析”领域的内容，需要熟练掌握偏微分方程以及精通将连续性方程离散化求解的编程能力。

-- B题是离散型（discrete）具体需要在编程上比较熟悉计算机的“算法与数据结构”。

-- C题是数据分析型（data insights），最好是有统计学、数理金融、量化分析相关背景的知识。

C题除了MATLAB、Python还可以是用无需编程的SPSS，也可能会用到R、STATS、SAS等统计软件。

ICM包括D、E、F三道题目：-- D题一般为运筹学或网络科学（operations research/network science），近几年网络科学是一个热门研究领域，算法、软件包括可视化的软件都很多。

-- E题是环境科学题（sustainability），大体上会集中在环境污染、资源短缺、可持续发展、生态保护等几个方面。

官方给出的六个问题的描述，对于选题有一定的提示作用，但是六道题目之间没有严格的模型划分，解答范围仍然很广，每道题所用模型、方法没有明显的界限。

因此小伙伴们在寒假先要摸清楚不同题目常用的模型算法、写作套路以及题目风格，比赛时根据自己队伍擅长的东西慎重选题。

02 近五年美赛A题特点小竞分析，在六道题目中，相对而言，A题是对同学们的数学模型素养以及建模能力要求较高的。

同时A题的专业性较强，非专业相关的同学对题目的理解较难。

例如2018年的A题：多跳HF无线电传播，这道赛题包含大量的专业名词，如电离层、最大可用频率、地面源、连续跳跃、局部介电常数等，大大增加了同学们对赛题的理解难度。

2019美赛数学建模题目（实用版）目录1.2019 美赛数学建模题目概述2.题目 A：无人机系统的设计与优化3.题目 B：植物病害检测与分类4.题目 C：非洲地区电力供应网络优化5.题目 D：城市交通信号控制优化6.总结正文【2019 美赛数学建模题目概述】2019 年美国大学生数学建模竞赛（MCM/ICM）共有六道题目，分别为A、B、C、D、E、F，涉及无人机系统设计与优化、植物病害检测与分类、非洲地区电力供应网络优化、城市交通信号控制优化等多个领域。

这些题目旨在考验参赛选手运用数学方法和技术解决实际问题的能力。

【题目 A：无人机系统的设计与优化】题目 A 要求参赛选手设计一种无人机系统，用于在城市和乡村地区进行环境监测、基础设施检查和灾难评估等任务。

选手需要考虑无人机的尺寸、重量、速度、航程、传感器和执行器等因素，通过建立数学模型来优化无人机系统的性能。

【题目 B：植物病害检测与分类】题目 B 要求参赛选手研究植物病害检测与分类的方法。

选手需要利用图像处理、机器学习和数据挖掘等技术，从植物叶片的图像中提取特征，建立分类模型，实现对植物病害的自动检测和分类。

【题目 C：非洲地区电力供应网络优化】题目 C 要求参赛选手研究非洲地区电力供应网络的优化问题。

选手需要分析非洲地区的电力需求和供应现状，建立电力网络模型，通过优化电力供应网络的结构和运行方式，提高电力供应的可靠性和经济性。

【题目 D：城市交通信号控制优化】题目 D 要求参赛选手研究城市交通信号控制的优化问题。

选手需要建立城市交通网络模型，分析交通流量和拥堵状况，设计优化信号控制策略，以提高道路通行能力和减少拥堵。

【总结】2019 美赛数学建模题目涵盖了多个领域，旨在考验参赛选手运用数学方法和技术解决实际问题的能力。

1993年美赛题（AB）A:Optimal CompostingAn environmentally conscious institutional cafeteria is recycling customers' uneaten food into compost by means of microorganisms. Each day, the cafeteria blends the leftover food into a slurry, mixes the slurry with crisp salad wastes from the kitchen and a small amount of shredded newspaper, and feeds the resulting mixture to a culture of fungi and soil bacteria, which digest slurry, greens, and papers into usable compost. The crisp green provide pockets of oxygen for the fungi culture, and the paper absorbs excess humidity. At times, however, the fungi culture is unable or unwilling to digest as much of the leftovers as customers leave; the cafeteria does not blame the chef for the fungi culture's lack of appetite. Also, the cafeteria has received offers for the purchase of large quantities of it compost. Therefore, the cafeteria is investigating ways to increase its production of compost. Since it cannot yet afford to build a new composting facility, the cafeteria seeks methods to accelerate the fungi culture's activity, for instance, by optimizing the fungi culture's environment (currently held at about 120 F and 100% humidity), or by optimizing the composition of the moisture fed to the fungi culture, or both.Determine whether any relation exists between the proportions of slurry, greens, and paper in the mixture fed to the fungi culture, and the rate at which the fungi culture composts the mixture. if no relation exists, state so. otherwise, determine what proportions would accelerate the fungi culture's activity. In addition to the technical report following the format prescribed in the contest instructions, provide a one-page nontechnicalrecommendation for implementation for the cafeteria manager. Table 1 shows the composition of various mixtures in pounds of each ingredient kept in separate bins, and the time that it took the fungi to culture to compost the mixtures, from the date fed to the date completely composted [table omitted].B:Coal-Tipple OperationsThe Aspen-Boulder Coal Company runs a loading facility consisting of a large coal tipple. When the coal trains arrive, they are loaded from the tipple. The standard coal train takes 3 hours to load, and the tipple's capacity is 1.5 standard trainloads of coal. Each day, the railroad sends three standard trains to the loading facility, and they arrive at any time between 5 A.M. and 8 P.M. local time. Each of the trains has three engines. If a train arrives and sits idle while waiting to be loaded, the railroad charges a special fee, called a demurrage. The fee is $5,000 per engine per hour. In addition, a high-capacity train arrives once a week every Thursday between 11 A.M. and 1 P.M. This special train has five engines and holds twice as much coal as a standard train. An empty tipple can be loaded directly from the mine to its capacity in six hours by a single loading crew. This crew (and its associated equipment) cost $9,000 per hour. A second crew can be called out to increase the loading rate by conducting an additional tipple-loading operation at the cost of $12,000 per hour. Because of safety requirements, during tipple loading no trains can be loaded. Whenever train loading is interrupted to load the tipple, demurrage charges are in effect.The management of the Coal Company has asked you to determine the expected annual costs of this tipple's loading operations. Your analysis should include the following considerations:How often should the second crew be called out?What are the expected monthly demurrage costs?If the standard trains could be scheduled to arrive at precise times, what daily schedule would minimize loading costs? Would a third tipple-loading crew at$12,000 per hour reduce annual operations costs?Can this tipple support a fourth standard train every day?。

1985~2014年美国大学生数学建模竞赛题目集锦目录1985 MCM A: Animal Populations (3)1985 MCM B: Strategic Reserve Management (3)1986 MCM A: Hydrographic Data (4)1986 MCM B: Emergency-Facilities Location (4)1987 MCM A: The Salt Storage Problem (5)1987 MCM B: Parking Lot Design (5)1988 MCM A: The Drug Runner Problem (5)1988 MCM B: Packing Railroad Flatcars (6)1989 MCM A: The Midge Classification Problem (6)1989 MCM B: Aircraft Queueing (6)1990 MCM A: The Brain-Drug Problem (7)1990 MCM B: Snowplow Routing (8)1991 MCM A: Water Tank Flow (8)1991 MCM B: The Steiner Tree Problem (8)1992 MCM A: Air-Traffic-Control Radar Power (9)1992 MCM B: Emergency Power Restoration (9)1993 MCM A: Optimal Composting (11)1993 MCM B: Coal-Tipple Operations (12)1994 MCM A: Concrete Slab Floors (12)1994 MCM B: Network Design (13)1995 MCM A: Helix Construction (14)1995 MCM B: Faculty Compensation (14)1996 MCM A: Submarine Tracking (14)1996 MCM B: Paper Judging (14)1997 MCM A: The Velociraptor Problem (15)1997 MCM B: Mix Well for Fruitful Discussions (16)1998 MCM A: MRI Scanners (17)1998 MCM B: Grade Inflation (18)1999 MCM A: Deep Impact (19)1999 MCM B: Unlawful Assembly (20)2000 MCM A: Air Traffic Control (20)2000 MCM B: Radio Channel Assignments (21)2001 MCM A: Choosing a Bicycle Wheel (22)2001 MCM B: Escaping a Hurricane's Wrath (An Ill Wind...) .. (23)2002 MCM A: Wind and Waterspray (25)2002 MCM B: Airline Overbooking (26)2003 MCM A: The Stunt Person (26)2003 MCM B: Gamma Knife Treatment Planning (27)2004 MCM A: Are Fingerprints Unique? (28)2004 MCM B: A Faster QuickPass System (28)2005 MCM A: Flood Planning (29)2005 MCM B: Tollbooths (29)2006 MCM A: Positioning and Moving Sprinkler Systems for Irrigation.. 29 2006 MCM B: Wheel Chair Access at Airports (30)2007 MCM A: Gerrymandering (31)2007 MCM B: The Airplane Seating Problem (32)2008 MCM A: Take a Bath (32)2008 MCM B: Creating Sudoku Puzzles (33)2009 MCM A: Designing a Traffic Circle (33)2009 MCM B: Energy and the Cell Phone (33)2010 MCM A: The Sweet Spot (35)2010 MCM B: Criminology (35)2011 MCM A: Snowboard Course (36)2011 MCM B: Repeater Coordination (36)2012 MCM A: The Leaves of a Tree (37)2012 MCM B: Camping along the Big Long River (37)2013 MCM A: The Ultimate Brownie Pan (38)2013 MCM B: Water, Water, Everywhere (38)2014 MCM A:The Keep-Right-Except-To-Pass Rule (39)2014 MCM B:College Coaching Legends (39)1985 MCM A: Animal PopulationsChoose a fish or mammal for which appropriate data are available to model it accurately. Model the animal's natural interactions with its environment by expressing population levels of different groups in terms of the significant parameters of the environment. Then adjust the model to account for harvesting in a form consistent with the actual method by which the animal is harvested. Include any outside constraints imposed by food or space limitations that are supported by the data.Consider the value of the various quantities involved, the number harvested, and the population size itself, in order to devise a numerical quantity that represents the overall value of the harvest. Find a harvesting policy in terms of population size and time that optimizes the value of the harvest over a long period of time. Check that the policy optimizes that value over a realistic range of environmental conditions.1985 MCM B: Strategic Reserve ManagementCobalt, which is not produced in the US, is essential to a number of industries. (Defense accounted for 17% of the cobalt production in 1979.) Most cobalt comes from central Africa, a politically unstable region. The Strategic and Critical Materials Stockpiling Act of 1946 requires a cobalt reserve that will carry the US through a three-year war. The government built up a stockpile in the 1950s, sold most of it off in the early 1970s, and then decided to build it up again in the late 1970s, with a stockpile goal of 85.4 million pounds. About half of this stockpile had been acquired by 1982.Build a mathematical model for managing a stockpile of the strategic metal cobalt. You will need to consider such questions as:▪How big should the stockpile be?▪At what rate should it be acquired?▪What is a reasonable price to pay for the metal?You will also want to consider such questions as:▪At what point should the stockpile be drawn down?▪At what rate should it be drawn down?▪At what price is it reasonable to sell the metal?▪How should it be allocated?Useful Information on CobaltThe government has projected a need ot 25 million pounds of cobalt in 1985.The U.S. has about 100 million pounds of proven cobalt deposits. Production becomes economically feasible when the price reaches $22/lb (as occurred in 1981). It takes four years to get operations rolling, and thsn six million pounds per year can be produced.In 1980, 1.2 million pounds of cobalt were recycled, 7% of total consumption.1986 MCM A: Hydrographic DataThe table below gives the depth Z of water in feet for surface points with rectangular coordinates X, Y in yards [table of 14 data points omitted]. The depth measurements were taken at low tide. Your ship has a draft of five feet. What region should you avoid within the rectangle (75,200) x (-50, 150)?The township of Rio Rancho has hitherto not had its own emergency facilities. It has secured funds to erect two emergency facilities in 1986, each of which will combine ambulance, fire, and police services. Figure 1 indicates the demand [figure omitted], or number of emergencies per square block, for 1985. The ―L‖ region in the north is an obstacle, while the rectangle in the south is a part with shallow pond. It takes an emergency vehicle an average of 15 seconds to go one block in the N-S direction and 20 seconds in the E-Wdirection. Your task is to locate the two facilities so as to minimize the total response time.▪Assume that the demand is concentrated at the center of the block and that the facilities will be located on corners.▪Assume that the demand is uniformly distributed on the streets bordering each block and that the facilities may be located anywhere on the streets.1987 MCM A: The Salt Storage ProblemFor approximately 15 years, a Midwestern state has stored salt used on roads in the winter in circular domes. Figure 1 shows how salt has been stored in the past. The salt is brought into and removed from the domes by driving front-end loaders up ramps of salt leading into the domes. The salt is piled 25 to 30 ft high, using the buckets on the front-end loaders.Recently, a panel determined that this practice is unsafe. If the front-end loader gets too close to the edge of the salt pile, the salt might shift, and the loader could be thrown against the retaining walls that reinforce the dome. The panel recommended that if the salt is to be piled with the use of the loaders, then the piles should be restricted to a matimum height of 15 ft.Construct a mathematical model for this situation and find a recommended maximum height for salt in the domes.1987 MCM B: Parking Lot DesignThe owner of a paved, 100' by 200' , corner parking lot in a New England town hires you to design the layout, that is, to design how the ``lines are to be painted. You realize that squeezing as many cars into the lot as possible leads to right-angle parking with the cars aligned side by side. However, inexperienced drivers have difficulty parking their cars this way, which can give rise to expensive insurance claims. To reduce the likelihood of damage to parked vehicles, the owner might then have to hire expert drivers for ``valet parking. On the other hand, most drivers seem to have little difficulty in parking in one attempt if there is a large enough ``turning radius'' from the access lane. Of course, the wider the access lane, the fewer cars can be accommodated in the lot, leading to less revenue for the parking lot owner.1988 MCM A: The Drug Runner ProblemTwo listening posts 5.43 miles apart pick up a brief radio signal. The sensing devices were oriented at 110 degrees and 119 degrees, respectively, when the signal was detected; and they are accurate to within 2 degrees. The signalcame from a region of active drug exchange, and it is inferred that there is a powerboat waiting for someone to pick up drugs. it is dusk, the weather is calm, and there are no currents. A small helicopter leaves from Post 1 and is able to fly accurately along the 110 degree angle direction. The helicopter's speed is three times the speed of the boat. The helicopter will be heard when it gets within 500 ft of the boat. This helicopter has only one detection device, a searchlight. At 200 ft, it can just illuminate a circular region with a radius of 25 ft.▪Develop an optimal search method for the helicopter.▪Use a 95% confidence level in your calculations.1988 MCM B: Packing Railroad FlatcarsTwo railroad flatcars are to be loaded with seven types of packing crates. The crates have the same width and height but varying thickness (t, in cm) and weight (w, in kg). Table 1 gives, for each crate, the thickness, weight, and number available [table omitted]. Each car has 10.2 meters of length available for packing the crates (like slices of toast) and can carry up to 40 metric tons. There is a special constraint on the total number of C_5, C_6, and C_7 crates because of a subsequent local trucking restriction: The total space (thickness) occupied by these crates must not exceed 302.7 cm. Load the two flatcars (see Figure 1) so as to minimize the wasted floor space [figure omitted].1989 MCM A: The Midge Classification ProblemTwo species of midges, Af and Apf, have been identified by biologists Grogan and Wirth on the basis of antenna and wing length (see Figure 1). It is important to be able to classify a specimen as Af of Apf, given the antenna and wing length.1. Given a midge that you know is species Af or Apf, how would you goabout classifying it?2. Apply your method to three specimens with (antenna, wing) lengths(1.24,1.80),(1.28,1.84),(1.40,2.04).3. Assume that the species is a valuable pollinator and species Apf is acarrier of a debilitating disease. Would you modify your classificationscheme and if so, how?1989 MCM B: Aircraft QueueingA common procedure at airports is to assign aircraft (A/C) to runways on afirst-come-first-served basis. That is, as soon as an A/C is ready to leave the gate (―push-back‖), the pilot calls ground control and is added to the queue. Suppose that a control tower has access to a fast online database with the following information for each A/C:▪the time it is scheduled for pushback;▪the time it actually pushes back; the number of passengers who are scheduled to make a connection at the next stop, as well as the time to make that connection; and▪the schedule time of arrival at its next stop Assume that there are seven types of A/C with passenger capacities varying from 100 to 400 in steps of50. Develop and analyze a mathematical model that takes into accountboth the travelers' and airlines' satisfaction.1990 MCM A: The Brain-Drug ProblemResearches on brain disorders test the effects of the new medical drugs – for example, dopamine against Parkinson's disease – with intracerebral injections. To this end, they must estimate the size and the sape of the spatial distribution of the drug after the injection, in order to estimate accurately the region of the brain that the drug has affected.The research data consist of the measurements of the amounts of drug in each of 50 cylindrical tissue samples (see Figure 1 and Table 1). Each cylinder has length 0.76 mm and diameter 0.66 mm. The centers of the parallel cylinders lie on a grid with mesh 1mm X 0.76mm X 1mm, so that the sylinders touch one another on their circular bases but not along their sides, as shown in the accompanying figure. The injection was made near the center of the cylinder with the highest scintillation count. Naturally, one expects that there is a drug also between the cylinders and outside the region covered by the samples.Estimate the distribution in the region affected by the drug.One unit represents a scintillation count, or 4.753e-13 mole of dopamine. For example, the table shows that the middle rear sylinder contails 28353 units. Table 1. Amounts of drug in each of 50 cylindrical tissue samples.Rear vertical sectionThe solid lines of the map (see Figure 1) represent paved two-lane county roads in a snow removal district in Wicomico County, Maryland [figure omitted]. The broken lines are state highways. After a snowfall, two plow-trucks are dispatched from a garage that is about 4 miles west of each of the two points (*) marked on the map. Find an efficient way to use the two trucks to sweep snow from the county roads. The trucks may use the state highways to access the county roads. Assume that the trucks neither break down nor get stuck and that the road intersections require no special plowing techniques.1991 MCM A: Water Tank FlowSome state water-right agencies require from communities data on the rate of water use, in gallons per hour, and the total amount of water used each day. Many communities do not have equipment to measure the flow of water in or out of the municipal tank. Instead, they can measure only the level of water in the tank, within 0.5% accuracy, every hour. More importantly, whenever the level in the tank drops below some minimum level L, a pump fills the tank up to the maximum level, H; however, there is no measurement of the pump flow either. Thus, one cannot readily relate the level in the tank to the amount of water used while the pump is working, which occurs once or twice per day, for a couple of hours each time. Estimate the flow out of the tank f(t) at all times, even when the pump is working, and estimate the total amount of water used during the day. Table 1 gives real data, from an actual small town, for oneday[ table omitted]. The table gives the time, in, since the first measurement, and the level of water in the tank, in hundredths of a foot. For example, after 3316 seconds, the depth of water in the tank reached 31.10 feet. The tank is a vertical circular cylinder, with a height of 40 feet and a diameter of 57 feet. Usually, the pump starts filling the tank when the level drops to about 27.00 feet, and the pump stops when the level rises back to about 35.50 feet.1991 MCM B: The Steiner Tree ProblemThe cost for a communication line between two stations is proportional to the length of the line. The cost for conventional minimal spanning trees of a set of stations can often be cut by introducing ―phantom‖ stations and then constructing a new Steiner tree. This device allows costs to be cut by up to13.4% (= 1- sqrt(3/4)). Moreover, a network with n stations never requires more than n-2 points to construct the cheapest Steiner tree. Two simple cases are shown in Figure 1.For local networks, it often is necessary to use rectilinear or ―checker-board‖ distances, instead of straight Euclidean lines. Distances in this metric are computed as shown in Figure 2.Suppose you wish to design a minimum costs spanning tree for a local network with 9 stations. Their rectangular coordinates are: a(0,15), b(5,20), c(16,24), d(20,20), e(33,25), f(23,11), g(35,7), h(25,0) i(10,3). You are restricted to using rectiline ar lines. Moreover, all ―phantom‖ stations must be located at lattice points (i.e., the coordinates must be integers). The cost for each line is its length.1. Find a minimal cost tree for the network.2. Suppose each stations has a cost w*d^(3/2), where d=degree of thestation. If w=1.2, find a minimal cost tree.3. Try to generalize this problem1992 MCM A: Air-Traffic-Control Radar PowerYou are to determine the power to be radiated by an air-traffic-control radar at a major metropolitan airport. The airport authority wants to minimize the power of the radar consistent with safety and cost. The authority is constrained to operate with its existing antennae and receiver circuitry. The only option that they are considering is upgrading the transmitter circuits to make the radar more powerful. The question that you are to answer is what power (in watts) must be released by the radar to ensure detection of standard passenger aircraft at a distance of 100 kilometers.1992 MCM B: Emergency Power RestorationPower companies serving coastal regions must have emergency response systems for power outages due to storms. Such systems require the input of data that allow the time and cost required for restoration to be estimated and the ―value‖ of the outage judged by objective criteria. In the past, Hypothetical Electric Company (HECO) has been criticized in the media for its lack of a prioritization scheme.You are a consultant to HECO power company. HECO possesses a computerized database with real time access to service calls that currently require the following information:▪time of report,▪type of requestor,▪estimated number of people affected, and▪location (x,y).Cre sites are located at coordinates (0,0) and (40,40), where x and y are in miles. The region serviced by HECO is within -65 < x < 60 and -50 < y < 50. The region is largely metropolitan with an excellent road network. Crews must return to their dispatch site only at the beginning and end of shift. Company policy requires that no work be initiated until the storm leaves the area, unless the facility is a commuter railroad or hospital, which may be processed immediately if crews are available.HECO has hired you to develop the objective criteria and schedule the work for the storm restoration requirements listed in Table 1 using their work force described in Table 2. Note that the first call was received at 4:20 A.M. and that the storm left the area at 6:00 A.M. Also note that many outages were not reported until much later in the day.HECO has asked for a technical rep ort for their purposes and an ―executive summary‖ in laymen's terms that can be presented to the media. Further, they would like recommendations for the future. To determine your prioritized scheduling system, you will have to make additional assumptions. Detail those assumptions. In the future, you may desire additional data. If so, detail the information desired.Table 1. Storm restoration requirements. (table incomplete)An environmentally conscious institutional cafeteria is recycling customers' uneaten food into compost by means of microorganisms. Each day, the cafeteria blends the leftover food into a slurry, mixes the slurry with crisp salad wastes from the kitchen and a small amount of shredded newspaper, and feeds the resulting mixture to a culture of fungi and soil bacteria, which digest slurry, greens, and papers into usable compost. The crisp green provide pockets of oxygen for the fungi culture, and the paper absorbs excess humidity. At times, however, the fungi culture is unable or unwilling to digest as much of the leftovers as customers leave; the cafeteria does not blame the chef for the fungi culture's lack of appetite. Also, the cafeteria has received offers for the purchase of large quantities of it compost. Therefore, the cafeteria is investigating ways to increase its production of compost. Since it cannot yet afford to build a new composting facility, the cafeteria seeks methods to accelerate the fungi culture's activity, for instance, by optimizing the fungi culture's environment (currently held at about 120 F and 100% humidity), or by optimizing the composition of the moisture fed to the fungi culture, or both. Determine whether any relation exists between the proportions of slurry, greens, and paper in the mixture fed to the fungi culture, and the rate at which the fungi culture composts the mixture. if no relation exists, state so. otherwise, determine what proportions would accelerate the fungi culture's activity. In addition to the technical report following the format prescribed in the contest instructions, provide a one-page nontechnical recommendation forimplementation for the cafeteria manager. Table 1 shows the composition of various mixtures in pounds of each ingredient kept in separate bins, and the time that it took the fungi to culture to compost the mixtures, from the date fed to the date completely composted [table omitted].1993 MCM B: Coal-Tipple OperationsThe Aspen-Boulder Coal Company runs a loading facility consisting of a large coal tipple. When the coal trains arrive, they are loaded from the tipple. The standard coal train takes 3 hours to load, and the tipple's capacity is 1.5 standard trainloads of coal. Each day, the railroad sends three standard trains to the loading facility, and they arrive at any time between 5 A.M. and 8 P.M. local time. Each of the trains has three engines. If a train arrives and sits idle while waiting to be loaded, the railroad charges a special fee, called a demurrage. The fee is $5,000 per engine per hour. In addition, a high-capacity train arrives once a week every Thursday between 11 A.M. and 1 P.M. This special train has five engines and holds twice as much coal as a standard train. An empty tipple can be loaded directly from the mine to its capacity in six hours by a single loading crew. This crew (and its associated equipment) cost $9,000 per hour. A second crew can be called out to increase the loading rate by conducting an additional tipple-loading operation at the cost of $12,000 per hour. Because of safety requirements, during tipple loading no trains can be loaded. Whenever train loading is interrupted to load the tipple, demurrage charges are in effect.The management of the Coal Company has asked you to determine the expected annual costs of this tipple's loading operations. Your analysis should include the following considerations:▪How often should the second crew be called out?▪What are the expected monthly demurrage costs?▪If the standard trains could be scheduled to arrive at precise times, what daily schedule would minimize loading costs? Would a third tipple-loading crew at $12,000 per hour reduce annual operations costs?▪Can this tipple support a fourth standard train every day?1994 MCM A: Concrete Slab FloorsThe U.S. Dept. of Housing and Urban Development (HUD) is considering constructing dwellings of various sizes, ranging from individual houses to large apartment complexes. A principal concern is to minimize recurring costs to occupants, especially the costs of heating and cooling. The region in which the construction is to take place is temperate, with a moderate variation in temperature throughout the year.Through special construction techniques, HUD engineers can build dwellings that do not need to rely on convection- that is, there is no need to rely on opening doors or windows to assist in temperature variation. The dwellings will be single-story, with concrete slab floors as the only foundation. You have been hired as a consultant to analyze the temperature variation in the concrete slab floor to determine if the temperature averaged over the floor surface can be maintained within a prescribed comfort zone throughout the year. If so, what size/shape of slabs will permit this?Part 1, Floor Temperature: Consider the temperature variation in a concrete slab given that the ambient temperature varies daily within the ranges given Table 1. Assume that the high occurs at noon and the low at midnight. Determine if slabs can be designed to maintain a temperature averaged over the floor surface within the prescribed comfort zone considering radiation only. Initially, assume that the heat transfer into the dwelling is through the exposed perimeter of the slab and that the top and bottom of the slabs are insulated. Comment on the appropriateness and sensitivity of these assumptions. If you cannot find a solution that satisfies Table 1, can you find designs that satisfy a Table 1 that you propose?and extend the analysis to temperature variation within the single-story dwelling. Can the house be kept within the comfort zone?Part 3, Cost of Construction: Suggest a design that considers HUD's objective of reducing or eliminating heating and cooling costs, considering construction restrictions and costs.1994 MCM B: Network DesignIn your company, information is shared among departments on a daily basis. This information includes the previous day's sales statistics and current production guidance. It is important to get this information out as quickly as possible. [Network diagram (with 5 nodes and 7 capacitated edges) omitted.] We are interested in scheduling transfers in an optimal way to minimize the total time it takes to complete them all. This minimum total time is called the makespan. Consider the three following situations for your company: [Three more network diagrams (on roughly 20 nodes each) omitted.]1995 MCM A: Helix ConstructionA small biotechnological company must design, prove, program and test a mathematical algorithm to locate ―in real time‖ all the inter sections of a helix and a plane in general positions in space. Design, justify, program and test a method to compute all the intersections of a plane and a helix, both in general positions (at any locations and with any orientations) in space. A segment of the helix may represent, for example, a helicoidal suspension spring or a piece of tubing in a chemical or medical apparatus. Theoretical justification of the proposed algorithm is necessary to verify the solution from several points of view, for instance, through mathematical proofs of parts of the algorithm, and through tests of the final program with known examples. Such documentation and tests will be required by government agencies for medical use.1995 MCM B: Faculty CompensationAluacha Balaclava College, and undergraduate facility, has just hired a new Provost whose first priority is the institution of a fair and reasonablefaculty-compensation plan. She has hired your consulting team to design a compensation system that reflects the following circumstances and principles: [Three paragraphs of details omitted] Design a new pay system, first without cost-of-living increases. Incorporate cost-of-living increases, and then finally, design a transition process for current faculty that will move all salaries towards your system without reducing anyone's salary. The Provost requires a detailed compensation system plan for implementation, as well as a brief, clear, executive summary outlining the model, its assumptions, strengths, weaknesses and expected results, which she can present to the Board and faculty. [A detailed table of current salaries is omitted.]1996 MCM A: Submarine TrackingThe world's oceans contain an ambient noise field. Seismic disturbances, surface shipping, and marine mammals are sources that, in different frequency ranges, contribute to this field. We wish to consider how this ambient noise might be used to detect large maving objects, e.g., submarines located below the ocean surface. Assuming that a submarine makes no intrinsic noise, develop a method for detecting the presence of a moving submarine, its speed, its size, and its direction of travel, using only information obtained by measuring changes to the ambient noise field. Begin with noise at one fixed frequency and amplitude.1996 MCM B: Paper JudgingWhen determining the winner of a competition like the Mathematical Contest in Modeling, there are generally a large number of papers to judge. Let's say there are P=100 papers. A group of J judges is collected to accomplish the。

2010-2014MCMProblems建模竞赛美赛题目重点2010 MCM ProblemsPROBLEM A: The Sweet SpotExplain the “sweet spot” on a baseball bat.Every hitter knows that there is a spot on the fat part of a baseball bat where maximum power is transferred to the ball when hit. Why isn’t this spot at the end of t he bat? A simple explanation based on torque might seem to identify the end of the bat as the sweet spot, but this is known to be empirically incorrect. Develop a model that helps explain this empirical finding.Some players believe that “corking” a bat (h ollowing out a cylinder in the head of the bat and filling it with cork or rubber, then replacing a wood cap enhances the “sweet spot” effect. Augment your model to confirm or deny this effect. Does this explain why Major League Baseball prohibits “corking”?Does the material out of which the bat is constructed matter? That is, does this model predict different behavior for wood (usually ash or metal (usually aluminum bats? Is this why Major League Baseball prohibits metal bats?MCM 2010 A题：解释棒球棒上的“最佳击球点”每一个棒球手都知道在棒球棒比较粗的部分有一个击球点，这里可以把打击球的力量最大程度地转移到球上。

历年美国数学建模竞赛题目1985 A J 动物群体的常微分方程.pdf1985 A J 动物群体的管理.pdf1985 A O An Effective Method for Harvesting Salmon.pdf1985 A O Grizzly Bears in Yellowstone National Park.pdf1985 A O Population Dynamics of Deer.pdf1985 A O Population Dynamics of The Peruvian Anchovy.pdf1985 B J B题的若干知识.pdf1985 B J 战略物资的存贮管理.rar1985 B O Managing a Cobalt Stockpile.pdf1985 B O The Problem of Managing a Strategic Reserve.pdf1986 A O Contour Interpolation of Random Data.pdf1986 A O Contouring of Hydrographic Data.pdf1986 A O Interpolating a Topographical Map of The Ocean Floor.pdf 1986 A O Spline Analysis of Hydrographic Data.pdf1986 A O 水道测量数据.pdf1986 B J 应急设施位置.pdf1986 B J 应急设施的优化选址问题.pdf1986 B J 应急设施的位置.pdf1987 A J 盐的贮存.pdf1987 A O The Salt Problem—Making a Mountain Out of Molehills.pdf 1988 A J 关于毒品走私船位置问题的数学模型.pdf1988 B J 两辆平板车的装载问题.pdf1988 B J 两辆铁路平板车的装货问题.pdf1988 B O Locating a Drug Runner Miami Vice Style.pdf1989 A J 判别分析和蠓虫分类.pdf1989 A J 蠓的分类.pdf1989 A O Neural-Network Approach to Classification Problems.pdf 1989 B J 飞机起飞的最优次序.pdf1990 A J 扩散问题的偏微分方程模型.pdf1990 A J 精神病用药问题.pdf1990 A J 试题分析.pdf1990 A O Error-Function Diffusion A Dopamine–Fick’s Model.pdf 1990 B J 扫雪问题.pdf1990 B J 扫雪问题的数学模型.pdf1991 A J 估计水箱的水流量.pdf1991 A J 估计水箱的水流量模型.pdf1991 A J 水塔水流量估计.pdf1991 A J 逼近观察数据的一些样条模型.pdf1991 B J 可靠网络中生成树的优化模型.pdf1991 B J 最小Steiner生成树.pdf1991 B J 最小费用斯坦纳树的构造.pdf1991 B O Finding Optimal Steiner Trees.pdf1991 B P 水塔流量估计.rar1992 B J 应急电力修复系统的修复计划.pdf1992 B O Development of an Emergency-Response System.pdf1993 A J 通过数学建模解决混合物转化为有机肥最佳过程问题.pdf1993 A O Coal-Tipple Operations.pdf1993 B J 倒煤台的操作方案.pdf1993 B J 煤车装卸系统的优化操作.PDF1994 A J 房屋隔热经济效益核算.pdf1994 B J 计算机网络的最小接通时间.pdf1994 B J 计算机网络的最短传输时间.pdf1994 B M 信息传递最少用时的数学模型.pdf1994 B O Talking Fast Finding the Makespan of a Communications Network.pdf1995 A C Author’s Commentary The Outstanding Helix Intersections Papers.pdf1995 A JC 单个的螺旋线.pdf1995 A O A Specialized Root-Finding Method for Rapidly Determining the Intersections of a Plane and a Helix.pdf1995 A O Planes and Helices.pdf1995 A O The Single Helix.pdf1995 B H 学院教师的付薪方案.pdf1995 B L 工资调整系统.pdf1995 B L 教员工资分配调整方案.pdf1995 B O How to Keep Your Job as Provost.pdf1995 B O Long-Term and Transient Pay Scale for College Faculty.pdf1995 B O Paying Professors What They’re Worth.pdf1995 B O The World’s Most Complicated Payroll.pdf1996 A J The Outstanding Helix Intersections Papers.pdf1996 A M 利用环境噪声场探测无自噪声潜艇.pdf1996 A O Detection of a Silent Submarine.pdf1996 A O Gone Fishin.pdf1996 A O How to Locate a Submarine.pdf1996 A O Imaging Underwater Objects with Ambient Noise.pdf1996 A P The Outstanding Submarine Location Papers.pdf1996 B J The Outstanding Contest Judging Papers A.pdf1996 B J The Outstanding Contest Judging Papers B.pdf1996 B JC 竞赛择优问题.pdf1996 B JC 竞赛评卷仿真.pdf1996 B M 快速评卷的方案设计.pdf1996 B M 竞赛评判问题.pdf1996 B O Judging a Mathematics Contest.pdf1996 B O Modeling Better Modeling Judges.pdf1996 B O Select the Winners Fast.pdf1996 B O The Inconsistent Judge.pdf1996 B O The Paper Selection Scheme Simulation Analysis.pdf1997 A H 恐龙的追逐捕食模型.pdf1997 A J The Outstanding Velociraptor Papers.pdf1997 A O A Three-Phase Model for Predator–Prey Analysis.pdf1997 A O Lunch on the Run.pdf1997 A O Modeling Optimal Predator and Prey Strategies.pdf1997 A O Pursuit–Evasion Games in the Late Cretaceous.pdf1997 A O The Geometry and the Game Theory of Chases.pdf1997 B J The Outstanding Discussion Groups Papers.pdf1997 B M The Well-Mixed Assignments.pdf1997 B M 有效讨论的最优混合解.pdf1997 B O A Greedy Algorithm for Solving Meeting Mixing Problems.pdf1997 B O An Assignment Model for Fruitful Discussions.pdf1997 B O Meetings Bloody Meetings.pdf1997 B O Using Simulated Annealing.pdf1997 B P The Outstanding Discussion Groups Papers.pdf1998 A J Judge's Commentary The Outstanding Scanner Papers.pdf1998 A M A Quick Algorithm for MRI Problem.pdf1998 A M Image Reconstruction in MRI.pdf1998 A O A Method for Taking Cross Sections of Three-Dimensional Gridded Data.pdf1998 A O A Model for Arbitrary Plane Imaging, or the Brain in Pain Falls Mainly on the Plane.pdf1998 A O A Tricubic Interpolation Algorithm for MRI Image Cross Sections.pdf1998 A O MRI Slice Picturing.pdf1998 A P Proposer's Commentary The Outstanding Scanner Papers.pdf1998 B H Place Students in Deciles Reasonably.pdf1998 B O A Case for Stricter Grading.pdf1998 B O Alternatives to the Grade Point Average for Ranking Students.pdf1998 B O Grade Infation A Systematic Approach to Fair Achievement Indexing.pdf1998 B O Judge's Commentary The Outstanding Grade Inflation Papers.pdf1998 B P Practitioner's Commentary The Outstanding Grade Inflation Papers.pdf1999 A H The Assessment Metheod of Impact.pdf1999 A O Antarctic Asteroid Effects.pdf1999 A O Asteroid Impact at the South Pole A Model-Based Risk Assessment.pdf1999 A O Not an Armageddon.pdf1999 A O The Sky is Falling.pdf1999 B H How to Calculate the Lawful Capacity in the Constraied Condition.pdf1999 B H How to Calculate the Lawful Capcity in the Constrained Condition .pdf1999 B J Judge's Commentary The Outstanding Lawful Capacity Papers.pdf1999 B O Determining the People Capacity of a Structur.pdf1999 B O Don't Panic.pdf1999 B O Hexagonal Unpacking.pdf1999 B O Room Capacity Analysis Using a Pair of Evacuation Models.pdf1999 B O Standing Room Only.pdf2000 A J Judge's Commentary The Outstanding Air Traffic Control Papers.pdf2000 A M Channel Assignment Strategies for Cellular Phone Systems.pdf2000 A M The Model For Measuring Complexity of Air Traffic Control Predicting and Adjusting Path Conflicts.pdf2000 A O Air Traffic Control.pdf2000 A O The Iron Laws of Air Traffic Control.pdf2000 A O The Safe Distance Between Airplanes and the Complexity of an Airspace Sector.pdf 2000 A O You Make the Call Feasibility of Computerized Aircraft Control.pdf2000 B J Author Judge's Commentary The Outstanding Channel Assignment Papers.pdf2000 B O A Channel Assignment Model The Span Without a Face.pdf2000 B O Groovin'with the Big Band(width).pdf2000 B O Radio Channel Assignments.pdf2000 B O Utilize the Limited Frequency Resources Efficiently.pdf2000 B O We're Sorry,You're Outside the Coverage Area.pdf2000 C J Judge's Commentary The Outstanding Elephant Population Papers.pdf2000 C O A Computational Solution for Elephant Overpopulation.pdf2000 C O EigenElephants When Is Enough,Enough.pdf2000 C O Elephant Population A Linear Model.pdf2001 A J Author-Judge's Commentary The Outstanding Bicycle Wheel Papers.pdf2001 A O A Systematic Technique for Optimal Bicycle Wheel Selection.pdf2001 A O Can’t Quite Put Our Finger On It.pdf2001 A O Selection of a Bicycle Wheel Type.pdf2001 A O Spokes or Discs.pdf2001 A P Choosing a Bicycle Wheel.zip2001 B M Strategies for Escaping a Hurricane's Wrath.zip2001 B H Hurricane Evacuation .pdf2001 B J Judge's Commentary The Outstanding Hurricane Evacuation Papers.pdf2001 B M What If Another Floyd Escaping a Hurricane's Wrath.pdf2001 B M When a Hard Wind Blows the Traffic Slows.pdf2001 B O Jammin'with Floyd A Traffic Flow Analysis of South Carolina Hurricane Evacuation.pdf2001 B O Please Move Quickly and Quietly to the Nearest Freeway.pdf2001 B O Project H.E.R.O. Hurricane Evacuation Route Optimization.pdf2001 B O The Crowd Before the Storm.pdf2001 B O Traffic Flow Models and the Evacuation Problempdf.pdf2001 B P 飓风来临的最佳疏散方案.rar2001 C J Judge’s Commentary The Outstanding Zebra Mussel Papers.pdf2001 C O A Multiple Regression Model to Predict Zebra Mussel Population Growth.pdf 2001 C O Identifying Potential Zebra Mussel Colonization.pdf2001 C O Waging War Against the Zebra Mussel.pdf2002 A J Judge’s Commentary The Outstanding Wind and Waterspray Papers.pdf2002 A M Blowin'in the Wind.pdf2002 A M Fountain Spray as a Particle Model.pdf2002 A M Woner Control Beautiful Foutain.rar2002 A O A Foul Weather Fountain.pdf2002 A O Simulating a Fountain.pdf2002 A O The Fountain That Math Built.pdf2002 A O Wind and Waterspray.pdf2002 B H How much to overbook this flight.zip2002 B J Judge’s Commentary The Outstanding Airline Overbooking Papers.pdf2002 B M Whole.rar2002 B O ACE is High.pdf2002 B O Overbooking on Airlines.pdf2002 B O Probabilistically Optimized Airline Overbooking Strategies.pdf2002 B O The Airline Overbooking Problem.pdf2002 B O Things That Go Bump in the Flight.pdf2002 C M If we Scrub our land too much we may lose the LIZARDs.rar2002 C M Life Model of Florida Scrub Lizard.rar2002 C O Cleaning Up the Scrub Saving the Florida Scrub Lizard.pdf2002 C O Where's the Scrub Aye,There's the Rub.pdf2003 A H Shaken, not Stirred.pdf2003 A M The Stunt Person.rar2003 A O Cardboard Comfortable When it comes to Crashing.pdf2003 A O Safe Landings.pdf2003 A O Thinking Outside the Box and Over the Elephant.pdf2003 A O You Too Can Be James Bond.pdf2003 A P Design and Stack the Cardboard Boxes.pdf2003 A P The design of the buffer cardboard boxes.pdf2003 B M Optimization of Stereotactic Radiosurgery Treatment Planning.pdf2003 B O Shelling Tumors with Caution and Wiggles.pdf2003 B P Shelling Procedure and Optimization by Simulated Annealing For Sphere Packing.pdf 2003 C H Aviation Baggage Screening.pdf2003 C H Security Screening at Airport.pdf2003 C H To Screen or Not.pdf2003 C M Aviation Baggage Screening Smart Approach to Screen.rar2003 C P Aviation Baggage Screening.pdf2004 A J Editor's Commentary Fingerprint Identification .pdf2004 A J Judge's Commentary The Outstanding Fingerprints Papers.pdf2004 A J Publisher's Editorial The Good Fight.pdf2004 A M Are Fingerprints Unique.pdf2004 A M Are Fingerprints Unique.rar2004 A M Fe-Fi-Fo Thumb.pdf2004 A O Can't Quite Put Our Finger On It.pdf2004 A O Not Such a Small Whorl After All.pdf2004 A O The Myth of The Myth of Fingerprints.pdf2004 A O Z Rule of Thumb Prints Beat DNA.pdf2004 B H a Faster QuickPass System.pdf2004 B H Magic Regulation Scheme for QuickPass System.pdf2004 B J Editor's Commentary Fingerprint Identification .pdf2004 B J Judges' Commentary The Quick Pass Fusaro Award Paper.pdf2004 B M Virtual Lines in Topoland with these Designs.pdf2004 B O A Myopic Aggregate-Decision Model for Reservation Systems in Amusement Parks.pdf 2004 B O An Adaptive Approach to Virtual Queing.pdf2004 B O Developing Improved Algorithms for QuickPass Systems.pdf2004 B O Developing Improved Algorithms for QuickPass Systems.pdf .pdf2004 B O KalmanQueue An Adaptive Approach to Virtual Queueing.pdf2004 B O Theme-Park Queueing Systems.pdf2004 B O Z Theme Park Simulation with a Nash-Equilibrium-Based Visitor Behavior Model.pdf 2004 B P Make Your Way Faster.pdf2004 B P Optimized QuickPass System.pdf2004 B P You Must Be at Least This Tall to Ride This Paper.pdf2004 C H ?IT Security Keep Hackers and Virus Out.pdf2004 C J Authors' Commentary The Outstanding Information Technology Security Papers.pdf 2004 C J Judge's Commentary The Outstanding Information Technology Security Papers.pdf 2004 C O Catch Thieves Online IT Security.pdf2004 C O Firewalls and Beyond Engineering IT Security.pdf2004 C O It's All About the Bottom Line.pdf2004 C O Making the CIA Work for You.pdf2005 A J Judge's Commentary The Outstanding Flood Planning Papers.pdf2005 A M One Two Step .pdf2005 A O Analysis of Dam Failure in the Saluda River Valley.pdf2005 A O From Lake Murray to a Dam Slurry.pdf2005 A O Through the Breach Modeling Flooding from a Dam Failure in South Carolina.pdf 2005 A O Z Catastrophic Consequences of Earthquake Destruction of the Saluda Dam.pdf 2005 B H For Whom the Booth Tolls .pdf2005 B H Is the Number of Tollbooths Optimal.pdf2005 B H Modeling Toll Plaza Behavior Using.pdf2005 B H Optimal Design of Toll Plaza.pdf2005 B H ?Pass the Plaza more Quickly .pdf2005 B J Judge's Commentary The Outstanding Tollbooths Papers.pdf2005 B M Giving Queueing the Booth.pdf2005 B O A Quasi-Sequential Cellular-Automaton Approach to Traffic Modeling.pdf2005 B O A Single-Car Interaction Model of Traffic for a Highway Toll Plaza.pdf2005 B O For Whom the Booth Tolls.pdf2005 B O Lane Changes and Close Following Troublesome Tollbooth Traffic.pdf2005 B O The Booth Tolls for Thee .pdf2005 B O The Booth Tolls for Thee.pdf2005 B O The Multiple Single Server Queueing System.pdf2005 B O Two Tools for Tollbooth Optimization.pdf2005 C H A Projection of Southeast Alaskan Salmon Populations.pdf2005 C H Between a Rockfish and a Hard Plaice.pdf2005 C H The future of “black gold”.pdf2005 C H When will the oil run out.pdf2005 C J Author's Commentary The Outstanding Exhaustible Resource Papers.pdf2005 C J Editorial Where Else to Publish.pdf2005 C J Judge's Commentary The Outstanding Exhaustible Resource Papers.pdf2005 C O Preventing the Hydrocalypse A Model for Predicting and Managing Worldwide Water Resource.pdf2005 C O The Coming Oil Crisis.pdf2005 C O The Petroleum Armageddon.pdf2006 A H A Simulated Annealing Approach to Irrigation.pdf2006 A H Minimizing Maintenance Cost for Hand-Moved Irrigation Systems.pdf2006 A H On Portable Irrigation Systems .pdf2006 A H Optimal Design of Irrigation Schedule.pdf2006 A J Judge's Commentary The Outstanding Irrigation Problem Papers.pdf2006 A M Optimizing a Handmove Sprinkler System .pdf2006 A M Piping Hot Weather.pdf2006 A M Positioning and Moving Sprinkler Systems for Irrigation.rar2006 A O Fastidious Farmer Algorithms (FFA).pdf2006 A O Fastidious Farmer Algorithms.pdf2006 A O Optimization of Irrigation.pdf2006 A O Z A Schedule for Lazy but Smart Ranchers.pdf2006 A O Z Developing Improved Algorithms for Irrigation Systems.pdf2006 A O Z Optimization of Irrigation.pdf2006 A O Z Sprinkle, Sprinkle, Little Yard.pdf2006 A O Z Sprinkler Systems for Dummies Optimizing a Hand-Moved Sprinkler System.pdf 2006 A P Positioning and Moving Sprinkler Systems for Irrigation .pdf2006 B H The Scheme of the Wheelchair Dispatch and Cost Analysis for Epsilon Airlines.pdf 2006 B H Transfer Suffers NEVER.pdf2006 B J Judges' Commentary The Fusaro Award Wheelchair Paper.pdf2006 B J Special Section on the MCM Judges Commentary The Fusaro Award Wheelchair Paper.pdf 2006 B M Minimal Costs for Serving Disabilities.pdf2006 B M Operational Research for Wheelchair Service Provided by Epsilon Airlines.pdf 2006 B M sly_airport.rar2006 B M When the Model Hits the Runway.pdf2006 B O A Simulation-Driven Approach for a Cost-Efficient Airport Wheelchair Assistance Service.pdf2006 B O Application of Min-Cost Flow to Airline Accessibility Services.pdf2006 B O Z A Simulation-Driven Approach for a Cost-Efficient Airport Wheelchair Assistance Service.pdf2006 B O Z Cost Minimization of Providing a Wheelchair Escort Service.pdf2006 B O Z Minimization of Cost for Transfer Escorts in an Airport Terminal.pdf2006 B O Z Profit Maximizing Allocation of Wheelchairs in a Multi-Concourse Airport.pdf 2006 C H Fighting against AIDS.pdf2006 C H War of the World Fight against AIDS.pdf2006 C J Author's Commentary The Outstanding HIV AIDS Papers.pdf2006 C J HIV The Math..pdf2006 C M AIDS A Global Crisis.pdf2006 C O AIDS Modeling a Global Crisis and Australia.pdf2006 C O Managing the HIV AIDS Pandemic 2006-2055.pdf2006 C O Managing the HIVAIDS Pandemic.pdf2006 C O The Spreading HIV AIDS Problem.pdf2006 C O The United Nations and the Quest for the Holy 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王教团（信息与计算科学）周朝卫（信息与计算科学）周龙飞（信息管理与信息系统）.pdf 2007 C J Author's Commentary The Outstanding Kidney Exchange Papers.pdf2007 C J Judges' Commentary The Outstanding Kidney Exchange Papers.pdf2007 C J Write Your Own Contest Entry.pdf2007 C M More Kidney Donors More Lives Can Be Saved.pdf2007 C O Analysis of Kidney Transplant System Using Markov Process Models.pdf2007 C O Optimizing the Effectiveness of Organ Allocation.pdf2007 C P Practitioner's Commentary The Outstanding Kidney Exchange Papers.pdf。

42016美赛题目(模拟赛题目)编辑整理：尊敬的读者朋友们：这里是精品文档编辑中心，本文档内容是由我和我的同事精心编辑整理后发布的，发布之前我们对文中内容进行仔细校对，但是难免会有疏漏的地方，但是任然希望（42016美赛题目(模拟赛题目)）的内容能够给您的工作和学习带来便利。

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2016年美赛A题热水澡一个人用热水通过一个水龙头来注满一个浴缸，然后坐在在浴缸中，清洗和放松。

不幸的是，浴缸不是一个带有二次加热系统和循环喷流的温泉式浴缸，而是一个简单的水容器。

过一会儿,洗澡水就会明显地变凉，所以洗澡的人需要不停地将热水从水龙头注入，以加热洗浴水。

该浴缸的设计是以这样一种方式，当浴缸里的水达到容量极限，多余的水通过溢流口泄流。

考虑空间和时间等因素，建立一个浴缸的水温模型，以确定最佳的策略，使浴缸里的人可以用这个模型来让整个浴缸保持或尽可能接近初始的温度，而不浪费太多的水。

使用你的模型来确定你的策略对浴缸的形状和体积，浴缸里的人的形状、体积、温度,以及浴缸中的人的运动等因素的依赖程度.如果这个人一开始用了一种泡泡浴剂加入浴缸，以协助清洗，这会怎样影响你的模型的结果？除了要求的一页MCM摘要提交之外,你的报告必须包括一页的为浴缸用户准备的非技术性的说明书来阐释你的策略，同时解释为什么洗澡水的温度得到均衡地保持是如此之难。

2016年美赛B题太空垃圾在地球轨道上的小碎片的数量已引起越来越多的关注.据估计，目前有超过500，000块的空间碎片，也被称为轨道碎片，由于被认为对空间飞行器是潜在的威胁而正在被跟踪。

2009年2月10日，俄罗斯卫星kosmos-2251和美国卫星iridium-33相撞之后，该问题受到了新闻媒体更广泛的讨论。