BPI翻译初稿

本科毕业论文外文翻译外文译文题目:不确定条件下生产线平衡：鲁棒优化模型和最优解解法学院：机械自动化专业：工业工程学号: 201003166045学生姓名: 宋倩指导教师：潘莉日期: 二○一四年五月Assembly line balancing under uncertainty: Robust optimization modelsand exact solution methodÖncü Hazır , Alexandre DolguiComputers ＆Industrial Engineering，2013,65：261–267不确定条件下生产线平衡：鲁棒优化模型和最优解解法安库·汉泽，亚历山大·多桂计算机与工业工程，2013，65：261–267摘要这项研究涉及在不确定条件下的生产线平衡，并提出两个鲁棒优化模型。

假设了不确定性区间运行的时间。

该方法提出了生成线设计方法,使其免受混乱的破坏。

基于分解的算法开发出来并与增强策略结合起来解决大规模优化实例.该算法的效率已被测试,实验结果也已经发表。

本文的理论贡献在于文中提出的模型和基于分解的精确算法的开发.另外，基于我们的算法设计出的基于不确定性整合的生产线的产出率会更高，因此也更具有实际意义。

此外,这是一个在装配线平衡问题上的开创性工作,并应该作为一个决策支持系统的基础。

关键字：装配线平衡；不确定性; 鲁棒优化；组合优化；精确算法1.简介装配线就是包括一系列在车间中进行连续操作的生产系统。

零部件依次向下移动直到完工。

它们通常被使用在高效地生产大量地标准件的工业行业之中。

在这方面，建模和解决生产线平衡问题也鉴于工业对于效率的追求变得日益重要。

生产线平衡处理的是分配作业到工作站来优化一些预定义的目标函数。

那些定义操作顺序的优先关系都是要被考虑的,同时也要对能力或基于成本的目标函数进行优化。

就生产（绍尔，1999）产品型号的数量来说，装配线可分为三类：单一模型（SALBP）,混合模型(MALBP）和多模式（MMALBP）。

目录先期事项 (5)适用范围 (5)信用证和修改的申请、信用证开立及修改 (5)总则 (8)缩略语 (8)证明书和证明、声明书和声明 (9)UCP600第19条至第25条的运输单据的副本 (10)更正与更改（统称“更正”） (11)寄送单据、通知等的快递收据、邮政收据或投邮证明 (13)日期 (13)单据中的空格栏 (16)UCP600运输条款不适用的单据 (16)UCP600未定义的用语 (17)单据出具人 (19)单据语言 (19)数学计算 (20)拼写或打字错误 (20)多页单据和附件或附文 (21)非单据化条件和数据矛盾 (21)正本和副本 (22)唛头 (24)签字 (25)单据名称及联合单据 (27)汇票及到期日计算 (28)基本要求 (28)付款期限 (28)付款到期日 (30)银行工作日、宽限期和付款延迟 (31)出具和签署 (32)金额 (33)背书 (34)更正与更改（统称“更正”） (34)以开证申请人为付款人的汇票 (34)发票 (35)发票名称 (35)发票出具人 (35)货物、服务或履约行为的描述及发票的其它一般性事项 (36)分期支款或装运 (39)涵盖至少两种不同运输方式的运输单据（“多式或联合运输单据”） (41)UCP600第19条的适用 (41)多式运输单据的出具、承运人、承运人身份的识别及签署 (42)装船批注、装运日期、收货、发送或接管地、装货港或出发地机场 (44)最终目的地、卸货港或目的地机场 (46)正本多式运输单据 (47)收货人、指示方、托运人和背书、被通知人 (47)转运、部分装运，以及提交多套多式运输单据时如何确定交单期 (49)清洁多式运输单据 (51)货物描述 (52)目的地交货代理人的名称与地址 (52)更正与更改（统称“更正”） (52)运费和额外费用 (53)凭多套多式运输单据放货 (54)提单 (55)UCP600第20条的适用 (55)提单的出具、承运人、承运人身份的识别及签署 (55)装船批注、装运日期、前程运输、收货地及装货港 (57)卸货港 (61)正本提单 (62)收货人、指示方、托运人和背书、被通知人 (62)转运、部分装运，以及提交多套提单时如何确定交单期 (64)清洁提单 (65)货物描述 (66)卸货港交货代理人的名称与地址 (66)更正和更改（统称“更正”） (67)运费和额外费用 (67)凭多套提单放货 (68)不可转让海运单 (70)UCP600第21条的适用 (70)不可转让海运单的出具、承运人、承运人身份的识别及签署 (70)装船批注、装运日期、前程运输、收货地及装货港 (72)卸货港 (76)正本不可转让海运单 (77)收货人、指示方、托运人和被通知人 (77)转运、部分装运，以及提交多套不可转让海运单时如何确定交单期 (79)清洁不可转让海运单 (80)货物描述 (81)卸货港交货代理人的名称与地址 (82)更正和更改（统称“更正”） (82)运费和额外费用 (82)租船提单 (84)UCP600第22条的适用 (84)租船提单的签署 (85)装船批注、装运日期、前程运输、收货地及装货港 (85)卸货港 (89)正本租船提单 (90)收货人、指示方、托运人和背书、被通知人 (91)部分装运以及提交多套租船提单时如何确定交单期 (93)清洁租船提单 (94)货物描述 (95)更正和更改（统称“更正”） (95)运费和额外费用 (95)凭多套租船提单放货 (96)租船合同 (97)空运单据 (98)UCP600第23条的适用 (98)空运单据的出具、承运人、承运人的身份识别及签署 (98)接受待运、装运日期和对实际发送日期的要求 (100)出发地机场和目的地机场 (101)正本空运单据 (101)收货人、指示方和被通知人 (102)转运、部分装运以及提及多套空运单据时如何确定交单期 (103)清洁空运单据 (105)货物描述 (105)更正和更改（统称“更正”） (106)运费和额外费用 (106)公路、铁路和内陆水路运输单据 (108)公路、铁路或内陆水路运输单据的出具、承运人、承运人的身份识别及签署 (108)装运地和目的地 (109)正本和第二联的公路、铁路或内陆水路运输单据 (110)收货人、指示方和被通知人 (111)转运、部分装运以及提及多套公路、铁路或内陆水路运输单据时如何确定交单期 (112)清洁公路、铁路或内陆水路运输单据 (114)货物描述 (115)更正和更改（统称“更正”） (115)运费和额外费用 (116)保险单据及承保范围 (117)UCP600第28条的适用 (117)保险单据的出具人、签署及正本保险单据 (117)日期 (119)保险金额和比例 (120)承保险别 (122)被保险人和背书 (122)保险单据的一般性条款和条件 (123)保费 (123)原产地证明 (125)基本要求和功能满足 (125)原产地证明的出具人 (125)原产地证明的内容 (126)装箱单 (128)基本要求和功能满足 (128)装箱单的出具人 (128)装箱单的内容 (128)重量单 (130)基本要求和功能满足 (130)重量单的出具人 (130)重量单的内容 (130)受益人证明 (132)基本要求和功能满足 (132)受益人证明的签署 (132)受益人证明的内容 (132)分析、检验、健康、植物检疫、数量、质量和任何其它证明（统称“证明”） (134)基本要求和功能满足 (134)证明的出具人 (135)证明的内容 (135)先期1事项Preliminary Considerations适用范围Scope of the publicationPara I:This publication is to be read in conjunction with UCP600 and not in isolation.本出版物应当结合UCP600进行解读，不应孤立解读。

英汉互译你方9月4日来函收到。

承告你们对肉类罐头有兴趣，并考虑试订。

We have received your letter of September 4 informing us that you find our canned meat satisfactory and that you consider placing a trial order with us.我们另邮寄样品一批，深信一旦你们有机会查看样品之后，定会承认该货品质优良，价格合理。

Under separate cover, we are sending you a range of samples and when you have a chance to examine them, we feel confident that you will agree that the goods are both excellent in quality and very reasonable in price.收到你公司5月14日询价，得悉你对我们手工制人造革手套感兴趣。

现将你所需的详细资料，具有插图的目录和价格单附寄给你。

We have received your enquiry of 14th May and learn of your interest in our handmade artificial leather gloves. We are enclosing our illustrated catalogue and price list giving the details you ask for.所附价格单和图解目录将给你提供有关你方最感兴趣的型号的具体情况。

The enclosed price list and illustrated catalogue will give you details of the model in which you are especially interested.我们确认已向你方电报下列商品实盘，以9月20日前复到有效。

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商务英语常用单词与写作带翻译商务英语常用单词与写作范文带翻译在真实的商务贸易中，常用的一些英语术语非常多，下面店铺带来关于商务英语常用单词与写作范文，供大家参考学习。

1、商業書信寫法(BUSINESS LETTER WRITING)1)、原則(Rules)--------Attention; interest;Desire;Action;2)、6C’s--------Clearness;correctness;conciseness;consideration;character;3)、Element(構成元素)------letterhead(company name;address，conact Number;);reference number;date;inside Address;salutation;2、報價(Quotation)報價是一種以特定條款提供產品的承諾。

詢價者如覺得價格合理，便可確認接受訂貨，因此報價者(OFFEROR)必須小心處理報價條款，如因錯報價格而無法供貨，則會對商譽有損。

報價通常是由買方提供予買方，即賣方報價(SELLING OFFER)，但亦有由買方提出價格，由賣方決定是否接受，稱為習方報價(BUYING OFFER)或出價(BID)。

一般報價可分實盤(FIRM OFFER/OFFER WITH ENGAGEMENT)及虛盤(No-firm /offer without engaement).實盤報價會詳細列明數量、交易條款及報價有效期，只要受盤人(OFFERENCE)在有效期內確認，便可達成交易。

如貨品價格經常浮動，或貨品供應不穩定，報價者可指明價屬虛盤，或加上保留條件，如以最后確認為准、以貨物尚未售出為准或報價可隨時變更等。

報價亦可以報價單(PRICE LIST)形式發出，此種報價并無特定對象，只作回復一般詢價時使用，并于報價單上說明以最后確認為准。

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外文文献翻译原文及译文标题：私人资本和公共资本外文翻译2019文献出处：Alvar Kangur, Chris Papageorgiou. European Economic Review, Volume 118, September 2019, Pages 296-311译文字数：4000 多字英文On the substitution of private and public capital in productionAlvar Kangur，Chris PapageorgiouAbstractMost macroeconomic models assume that aggregate output is generated by a specification for the production function with total physical capital as a key input. Implicitly this assumes that private and public capital stocks are perfect substitutes. In this paper, we test this assumption by estimating a nested-CES production function whereas the two types of capital are considered separately along with labor as inputs. The estimation is based on our newly developed dataset on public and private capital stocks for 151 countries over a period of 1960–2014 consistent with Penn World Table version 9. We find evidence against perfect substitutability between public and private capital, especially for emerging and LIDCs, with the point estimate of the elasticity of substitution estimated closely around 3.Keywords: Public capital, Private capital, Elasticity of substitution, Production functionIntroductionAfter two generations of research papers focused on identifying the effect of public capital on economic activity, a broad consensus has beenreached pointing to the favorable contributions of public capital to economic growth especially in early stages of economic development. Bom and Lighthart (2014) provide one way of summarizing these results by means of a meta-analysis using 578 estimates of output elasticity of public capital estimates. This analysis finds a long-run elasticity in the order of 12%, that increases to about 19% for core public capital and exhibits substantial heterogeneity across various dimensions, including income and regional differences. Allowing for cross-country heterogeneity, Calderón et al. (2015) find that the elasticity of output with respect to infrastructure capital ranges between 0.07 and 0.10. Kangur and Papageorgiou (2017) document the evolution of the literature throughout the two generations of research papers. The first generation dates back to the seminal work of Aschauer (1989) which documents substantial growth effects of public capital and was later refined throughout the second generation of research on various methodological grounds as summarized extensively by Romp and de Haan (2007).Yet, macroeconomic models have largely assumed that public and private capital are perfectly substitutable in the aggregate production function or they are combined under the straitjacket of Cobb–Douglas aggregation function. Whether these prevalent assumptions are valid is an empirical question that this paper aims to answer by estimating the elasticity of substitution (ES) of the two types of capital.This paper makes two contributions. First, we construct public and private investment and capital stock series for 151 countries covering 1960–2014. In doing so we ensure that at any point in time public and private investment and amortization levels are ex ante consistent with the aggregate economy-wide capital stock, investment, and amortization series reported in the Penn World Table (PWT) version 9. By treating these economy-wide series as observables and imposing the consistency requirements we are able to avoid making assumptions on historical or steady-state public and private investment growth rates typically required by existing approaches.Second, with this new capital stock data at hand we examine whether public and private capital are complementary or substitutable in the aggregate production process. This is important as it challenges existing formulations of production functions that favor either a Cobb–Douglas aggregation between the two types of capital or, even more extreme, no disaggregation of the two types of capital thus implying that they are perfect substitutes. We show that for the entire sample of countries neither of the dominant assumptions in the literature are supported by the evidence which obtains a point estimate of the ES between public and private capital of around 3. Furthermore, there exists substantial heterogeneity in these estimates across groups of countries the ES is shown to be higher for emerging countries than LIDCs while foradvanced countries it is found to be well characterized by a Cobb–Douglas technology. These results hold well under various robustness tests including on alternative production structure, methodological approaches, and data sources.MethodologyConstruction of public capital stocks for a large set of countries that would be comparable across-countries as well as to the concepts of private or aggregate economy-wide capital stocks generally used in growth models is a notoriously hard task. While most empirical applications accumulate capital stocks with the perpetual inventory method, the practitioners have to overcome numerous obstacles due to lack of data on investment flows, measurement errors, estimates of (time- varying) depreciation rates, as well as methodological complexities in setting the initial conditions.Many studies avoid these challenges by using a variety of measures of physical infrastructure such as kilometers of paved roads or kilowatts of electricity-generating capacity that generally are more readily available. At the same time these are only partial measures of the aggregate public capital stock as they do not correct for quality, capture only some core aspects of public infrastructure, are not necessarily additive in terms of investment and amortization flows, and thus do not capture the overall general government activities. As such, mapping the estimates of publiccapital productivity or any deep parameters obtained from various measures of physical capital into production functions is not straightforward. Accumulating the public capital stocks with the perpetual inventory method can be problematic as well.To overcome the difficulties in setting the initial condition for the public sector capital stock Kamps (2006) applies an “asymptotic limit” approach by setting the capital stock in 1860—a 100 years before the start of the empirical estimation period—to zero and using an artificial investment series over a period of 1860–1959 to get an initial capital stock estimate for 1960. The artificial investment series is constructed by applying an average investment growth over a period for which the data are available (1960–2001 in case of Kamps, 2006) backwards from the earliest year when the actual data are available. His sensitivity tests show that errors from the starting condition in 1860 and from assuming an artificial investment series diminish over time and do not have material effect on the dynamics of capital stock from 1960 onwards or on the econometric estimates of public capital elasticities.The “asymptotic” approach has been applied successfully in several studies. Arslanalp et al. (2010) derive the capital stocks for 48 countries using public–private investment shares from the IMF World Economic Outlook (WEO) database, whereas Gupta et al. (2014) extend the coverage to 122 developing countries and introduce an efficiency-adjustment for 52 middle- and low-income countries. The approach still has two distinctive features that can lead to measurement errors. First, the long-term average investment growth rate is not always the best proxy for the historical average, especially in countries undergoing structural changes. Second, when the aggregate capital stock is observed, it can be difficult to impose ex ante consistency between the levels of observable aggregate investment and amortization series with their private and public components.In this paper we resort to an alternative approach that derives the unobserved public and private capital stocks from the observable economy-wide capital stocks and amortization levels, as well as respective investment shares of the components. The methodology used to construct the private and public capital stock series follows that in Collier et al. (2001), Kamps (2006), Arslanalp et al. (2010), and Gupta et al. (2014). That we make an extra effort here to make our capital stock series consistent with those in PWT9, is because PWT has been widely considered as the gold standard for empirical work, and also because of the PWT9’s methodological advantages in their use of the perpetual inventory method (see Feenstra et al., 2015, Online Appendix, pp. 9–21).To sum up, we estimate the elasticity of substitution between private and public capital using our newly constructed panel data. We find that private and public capital are highly but not perfectly substitutable, withthe point estimate of the elasticity of substitution around 3. This finding is important because most macroeconomic models assume that aggregate output is generated by a production function specification with total physical capital as a key input. Implicitly this assumes that private and public capital stocks are perfect substitutes. However, since they are highly but not perfectly substitutable, neither a Leontief nor a Cobb–Douglas type aggregation should be applied to the private and public capital stocks in a production function.Sensitivity analysisIn this section, we conduct several robustness checks. First, we examine whether our baseline results are sensitive to alternative data frequencies, or to the inclusion of time fixed effects. Next, we examine whether our baseline results are robust to alternative measures of labor. Finally, we compute the standard errors using alternative bootstrapping methods.The baseline results above are estimated based on 3-year averaged data. The reason for using 3-year averaging rather than annual frequency data is twofold: first, it mitigates the business-cycle effects and other potential noise in the annual frequency data and second, it provides large sample for consistent estimation. However, we recognize that the choice of 3-year averaging is arbitrary. To the best of our knowledge, there is no method to determine the optimal data frequency in the estimation ofaggregate production functions. As a first robustness check, we investigate whether our baseline results are robust to alternative data frequencies.In the baseline estimation, we assume a constant and Hicks-neutral technical progress along time and there are no time fixed effects. One concern is that the technological growth rate can be changing over time, which can be an issue for our estimation considering that we use a large panel with a long time span. To address this concern, we include time fixed effects into the baseline estimates. Due to the complexities of NLLS estimation, the iterative optimization procedure has difficulties in converging when we include fixed effects for each single time period. As an alternate, we include time fixed effects for aggregate time periods.Controlling for human capitalIn the baseline estimates above, labor input is measured directly as total employment. One concern is that labor and labor income might not be properly measured, especially in emerging economies and LIDCs, as Gollin (2002) discussed. The mismeasure of labor input might affect the estimated elasticity of substitution and distribution between the composite capital and labor, and further affects the estimated elasticity of substitution between private and public capital. Krusell et al. (2000) find that the relative quantity of skilled labor has increased substantially since 1980, and controlling for capital-skill complementarity affects productionfunction estimations. To address this concern, we weight total employment with human capital. The human capital index is retrieved directly from PWT, and it measures the average schooling and returns to education. Instead of including total employment, we multiply total employment with the human capital index.EndogeneityIn order to address concerns over endogeneity and transmission bias we next resort to macro-econometric techniques. For this purpose we resort to a Kmenta (1967)linearized approximation to public–private capital CES nested in the Cobb–Douglas production function that allows the use of linear regression methods.Panel unit root tests overwhelmingly fail to reject the unit root in all four variables of interest: real GDP, real private capital stock, real public capital stock and the square of a ratio of public to private capital (all expressed as ratios to employment and in natural logs). At the same time, a battery of panel cointegration tests due to Pedroni, Westerlund, and Kao reject the null hypothesis of no cointegration between all four variables decisively only for emerging economies; cointegration results for LIDC are more mixed whereas for advanced countries several test specifications fail to reject the null. Estimation results are therefore most meaningful for emerging countries. We estimate the parameters of the linearized Kmenta CES function with panel group mean FMOLS developed by Pedroni,2000, Pedroni, 2001 that allows for complete endogeneity (using internal instruments) as well as heterogeneity, and includes time effects to control for simple cross-sectional dependence. The results support public–private capital substitutability for emerging countries as well as for the full sample. Results are available upon request.In summary, we find strong evidence of substitutability between public and private capital, with a point estimate of the elasticity of substitution around 3. This result is driven by emerging economies and LIDCs, and it is more robust in emerging economies. For advanced economies, estimation shows no significant results. These results hold up pretty well to a series of robustness tests.ConclusionIn this paper we find evidence against the perfect substitutability between public and private capital assumed in the literature. Using a nested CES aggregate production function that incorporates public and private capital along with labor as inputs, we obtain a point estimate of the elasticity of substitution between the two types of capital around 3. The estimation is based on a newly developed dataset on public and private capital stocks for 151 countries over a period of 1960–2014 consistent with Penn World Table version 9.Our results provide some leads about growth policies. First, abstracting from other factors of production, high substitution betweenpublic and private capital implies that, as the capital stock increases, both marginal and average products approach to a positive constant, rather than zero as prescribed by Inada conditions. Second, the empirical estimates which show that public and private capital in the production of developing economies is more substitutable than in advanced countries, are consistent with the idea that advanced economic systems require provision of public capital that is more complementary to highly specialized private sector capital, while in less advanced countries public capital is needed to fill gaps in private sector which is still quite underdeveloped. While our estimates do not allow us to identify specific channels or causes of capital substitutability, we hope that they provide a starting point to a promising line of future research.中文论生产中私人资本和公共资本的替代摘要大多数宏观经济模型假设总产出是由生产函数的规范产生的，而总实物资本是关键输入。