INDUSTRIAL PRODUCTION IN GERMANY AND AUSTRIA： A CASE STUDY IN STRUCTURAL TIME SERIES MODELLING

Industrial production series are volatile and often cyclical. Time series models can be used toestablish certain stylized facts, such as trends and cycles, which may be present in these series. Incertain situations, it is also possible that common factors, which may have an interesting interpretation,can be detected in production series. Series from two neighboring countries with close economicrelationships, such as Germany and Austria, are especially likely to exhibit such joint stylized facts.     

考虑休班公平及同班次约束的呼叫中心排班优化问题

国内呼叫中心企业制定人力排班表时,越来越关注员工诉求及体现人性化管理理念.考虑坐席人员双休日休班公平性和周内工作日上班时间规律性,构建以多周为计划周期的呼叫中心排班优化问题整数规划模型.在对问题结构和优化性质分析基础上,提出构造性启发式算法.使用企业实例数据对模型和算法性能进行评估.计算结果表明规划模型只适于求解小规模问题最优解,而启发式算法能够以小计算成本获得较大规模问题优化解.最后计算分析得出了这些员工诉求因素对排班人力成本影响的量化结果.     

多类对象非线性流水线的无冲突调度规划

本文提出一种为多类型对象服务的非线性流水系统的调度规划方法。该方法给出冲突矩阵表示对象流入流水线的限制，通过启发式搜索寻找面向目标优化的调度策略。获得的调度策略能满足服务过程无冲突无阻塞的要求。     

特殊一维背包问题的降维替换算法研究

对问题单约束0-1线性整数规划问题(0-1ILP,背包问题)的特性进行了分析,设计了问题求解的算法--降维替换算法(线性规划求解与特殊启发式相结合的方法).     

一个批处理机随机调度模型

以零售业企业（超市、百货商店、仓储式商场等）进货为背景新建立一个批处理机随机调度模型．模型中含两个问题，首先分别将它们转化成了与其等价的确定优化问题，接着给出了确定优化问题的最优调度的性质，最后基于性质给出了求解确定优化问题的算法。     

无人侦察机路径规划方法研究

将无人机的侦察任务分为点状,线形和区域三类典型侦察任务.综合考虑探测传感器的特性,针对线形侦察任务,提出侦察走廊的概念;改进启发函数,基于A*算法有效解决点状、线形侦察任务路径规划问题;考虑飞机转弯半径限制,提出解决探测盲区的方法;针对带禁飞区的复杂区域搜索侦察任务,将全区域分割成若干无禁飞区的子区域,采用深度优先遍历算法,获得子区域的搜索顺序,在保证侦察无遗漏的前提下,利用往复前进式搜索方式,就可对区域侦察任务进行全区域覆盖的路径规划.仿真结果证实了规划方法的合理性和有效性.     

考虑工作量均衡的成品油二次配送车辆路径问题

为避免工作量分配不均,研究了考虑工作量均衡的成品油二次配送车辆路径问题。以总配送成本极小化和不同车辆路径长度之差极小化为目标,建立了双目标混合整数规划模型;并设计了变邻域禁忌搜索启发式算法。利用改进的Solomon＿I1插入算法求出使总配送成本尽量小的初始解;再利用变邻域禁忌搜索算法改进初始解,得到近似最优解。模拟计算结果显示,通过变邻域禁忌搜索算法改进后的解,总配送成本仅增加6.2%,车辆路径长度差值降低了45%,验证了算法的有效性。     

A CASE FOR SUSTAINABLE SECURITY SYSTEMS ENGINEERING： INTEGRATING NATIONAL, HUMAN, ENERGY AND ENVIRONMENTAL SECURITY

In the wake of the September 11, 2001 terrorist attacks, there is a growing sense of insecurity felt by many citizens around the world. Sustainable security, with roots in the sustainable development and human security literature, seeks positive transformations for the co-evolving and mutually dependent human-environmental condition by integrating (and subsuming) national, human, environmental, and energy security concerns and capitalizing on opportunities provided by human creativity, diplomatic openings, modernization and environmental change. The field of Sustainable Security Systems Engineering is proposed for protecting, restoring, designing, and implementing a set of integrated natural and man-made processes that equitably and responsibly meet the biophysical needs of human communities, while maintaining long-term security, respecting financial constraints, meeting ecological limits, and improving institutional arrangements for transparent and effective governance. Scenario planning is shown to help promote sustainable security by identifying the preconditions of instability and helping to proactively address them in an increasingly complex and uncertain world. The six papers published in this featured collection cross policy domains, geographic, political, and sectoral boundaries and were discussed at forums sponsored by the Systems Engineering and Global Policy group. Collectively, they demonstrate the quality, breadth and depth of systems engineering methodologies that are used to promote sustainable security.     

A NESTED PARTITIONS FRAMEWORK FOR SOLVING LARGE-SCALE MULTICOMMODITY FACILITY LOCATION PROBLEMS

Large-scale multicommodity facility location problems are generally intractable with respect to standard mixed-integer programming (MIP) tools such as the direct application of general-purpose Branch & Cut (BC) commercial solvers i.e. CPLEX. In this paper, the authors investigate a nested partitions (NP) framework that combines meta-heuristics with MIP tools (including branch-and-cut). We also consider a variety of alternative formulations and decomposition methods for this problem class. Our results show that our NP framework is capable of efficiently producing very high quality solutions to multicommodity facility location problems. For large-scale problems in this class, this approach is significantly faster and generates better feasible solutions than either CPLEX (applied directly to the given MIP) or the iterative Lagrangian-based methods that have generally been regarded as the most effective structure-based techniques for optimization of these problems. We also briefly discuss some other large-scale MIP problem classes for which this approach is expected to be very effective. This work is supported partly by the National Science Foundation under grant DMI-0100220, DMI-0217924, by the Air Force of Scientific Research under grant F49620-01-1-0222, by Rockwell Automation, and by John Deere Horicon Works. Leyuan Shi is a Professor of the Department of Industrial Engineering at University of Wisconsin-Madison. She received her Ph.D. in Applied Mathematics from Harvard University in 1992, her M.S. in Engineering from Harvard University in 1990, her M.S. in Applied Mathematics from Tsinghua University in 1985, and her B.S. in Mathematics from Nanjing Normal University in 1982. Dr. Shi has been involved in undergraduate and graduate teaching, as well as research and professional service. Dr. Shi’s research is devoted to the theory and applications of large-scale optimization algorithms, discrete event simulation and modeling and analysis of discrete dynamic systems. She has published many papers in these areas. Her work has appeared in Discrete Event Dynamic Systems, Operations Research, Management Science, IEEE Trans., and, IIE Trans. She is currently a member of the editorial board for Journal of Manufacturing & Service Operations Management, is an Associate Editor of Journal of Discrete Event Dynamic Systems, and an Associate Editor of INFORMS Journal on Computing. Dr. Shi is a member of IEEE and INFORMS. Robert R. Meyer received a B.S. in Mathematics from Caltech and an M.S. and a Ph.D. in Computer Sciences from the University of Wisconsin-Madison. He is currently Professor of Computer Sciences at the University of Wisconsin-Madison, where he has been on the faculty since 1973. He has co-edited six volumes of optimization conference proceedings and written more than 80 articles focusing on areas such as nonlinear network optimization, parallel decomposition algorithms for large-scale optimization, genetic algorithms, and theory and applications of discrete optimization. Mehmet Bozbay is a research assistant in the Department of Industrial Engineering at University of Wisconsin-Madison. He is currently working towards his Ph.D. degree in Industrial Engineering. He received M.S. degrees in Industrial Engineering and Computer Sciences from University of Wisconsin-Madison, and a B.S. degree in Mathematics from Beloit College. He has been dealing with real-life supply chain optimization problems for the last 4 years. He is a member of INFORMS. Andrew J. Miller is an Assistant Professor of the Department of Industrial Engineering at the University of Wisconsin—Madison. He received his Ph.D. in Industrial Engineering from the Georgia Institute of Technology in 1999, his M.S. in Operations Research from the Georgia Institute of Technology in 1996, and his B.S. in Mathematics from Furman University in 1994. Dr. Miller has been involved in research, undergraduate and graduate teaching, and professional service, as well as in some software prototyping and development. Dr. Miller’s research focuses on theoretical and computational aspects of mixed integer programming, and on its application to areas in production planning, supply chain design, and other fields. He has published several papers in these areas, including articles in Mathematical Programming, Operations Research, and European Journal of Operations Research. He has refereed numerous articles for the journals mentioned above, as well as for Management Science, Annals of Operations Research, and others. Dr. Miller is a member of INFORMS and of the Mathematical Programming Society.     

带有限容量缓冲库的多目标柔性作业车间调度优化

研究一类从无缝钢管生产实际中提炼出的作业车间调度问题.该问题具有生产工序间存在有限容量缓冲库,生产工艺路径柔性选择,生产设备需要转换时间,生产调度多目标等特点.针对具有这些特点的调度问题,构建了混合整数规划模型.鉴于其NP-hard性,设计改进的遗传算法进行求解,进而提出辅以局部搜索优化算法的方法,并通过企业生产实际数据比较和验证算法的性能及有效性.该模型和算法已被用于无缝钢管生产作业计划软件系统的开发,并在实际运用中取得了良好的效果,对各大钢管企业的生产调度均具有一定的实际指导意义.     

堆区混贝的堆场场吊调度模型与算法

为提高集装箱码头堆场场吊作业效率,研究了堆场单堆区混贝条件下的场吊调度问题.在单堆区内集装箱混贝堆放的前提下,提出了堆场场吊装卸作业时间窗约束、作业次序依赖的设备调整时间及堆场空间约束等,并在此基础上建立了整数规划模型.针对这一模型设计了改进禁忌搜索算法对问题进行求解.最后通过数值实验表明改进后的算法在对大规模问题求解时具有良好的效果,且算法效率较高.     

A case study for advanced planning and scheduling (APS)

This paper presents a case study for the advanced planning and scheduling (APS) problem encountered in a light source manufacturer. The APS problem explicitly considers due dates of products, operation sequences among items, and capacity constraints of the manufacturing system. The objective of the problem is to seek the minimum cost of both production idle time and tardiness or earliness penalty of an order. An intelligent heuristic is applied to the problem, and the results demonstrate that significant production performances can be achieved while ensuring customer satisfaction as opposed to normal practices followed in the company relying on human expertise.     

超大规模管理优化问题的求解:城市小区粪渣清运排班案例研究

深圳市罗湖区小区粪渣清运排班优化为超大规模的实际管理优化问题.以该问题为案例,探索超大规模优化问题可行的求解方法.建立了城市小区粪渣清运排班优化模型,根据"贪婪"规则,设计了基于构造规则的启发式算法.通过小规模算例验证了算法的有效性.将该算法应用于案例中的实际问题,取得了满意结果.研究表明,对于实际的超大规模优化问题,可依据问题自身的特征,基于最质朴的贪婪规则,设计合适的启发式算法求解.该研究为类似的超大规模优化问题的求解提供了可供选择的思路.     

大数据视角下的采购风险评估--基于某服务采购企业的案例分析

在经济全球化和专业化分工的背景下,企业供应链管理的各个环节面临着越来越大的风险.跨界的大数据及其分析技术通过提升数据的可视性,为企业的风险管理带来了新的工具和手段.本文聚焦企业运营管理中的采购环节,分析如何利用大数据来评估采购风险.通过梳理一家典型服务采购企业采购流程中面临的各种风险,我们提出了一个5+X的采购风险分类框架;其中包括环境风险、竞争风险、道德风险、财务风险、履约风险以及内控风险.我们给出了测度各类风险可能的数据来源以及处理方法.通过一个案例研究我们展示了基于大数据的采购风险评估的具体实施.     

商业模式PNMP-CET@I反馈调节分析模型:蚂蚁金服案例

本文认为商业模式创新是一个反复调整的过程,基于商业模式冰山理论和CET@I方法论,构建了商业模式PNMP-CET@I反馈调节分析模型.该模型综合考虑各类环境因素,基于集成的思想对各要素进行综合集成分析,进而对现有的商业模式进行优化调整.应用本文提出的模型进行案例研究,集成分析结果得出蚂蚁金服的商业模式优于传统金融的商业模式,希望给互联网金融企业和传统金融企业的发展提供新的思路和管理启示.     

Refinery constructors incorporated: A case study in adaptation to advanced telecommunications technology

This paper illustrates the application of a broadly based approach to the implementation of an advanced communications system in an international setting. The failure of an initial implementation is discussed. The subsequent removal of the failed system and redesign of the second implementation process with overt consideration of sociotechnical factors are discussed. This article challenges a conventional view that focusing on technology, e.g., hardware and software, is the major determinant of success in implementation. The intrusion of computer-based technology into the office environment mandates considering the sociotechnical aspects of implementation such as work-group impacts, job design issues, and organizational adaptation. This study, in a field setting, describes the results of socialand technical considerations in systems implementation and illustrates the bottom-line impact of a specific investment in information technology in a large multinational corporation.     

基于最优信用特征组合的违约判别模型——以中国A股上市公司为例

违约判别是信用风险评估的一种方式，提高违约判别精度一直是学界和业界重点关注的问题.本文从最优信用特征组合而不是最优指标组合的角度建立违约判别模型，提高违约判别精度.本文的创新有三个方面：一是以信息值最大为目标建立优化模型，将指标数据划分成能最大区分违约状态的多个信用特征.二是采用弹性网回归对信用特征进行遴选，反推违约判别误差最小的最优信用特征组合.三是以组间离散度与组内离散度之比最大为目标，构建数学规划，反推一组权重，得到线性判别方程.本文基于2000-2017年共2169家中国A股上市公司的数据进行实证，研究表明经过特征划分的线性判别分析、K近邻、支持向量机等模型的精度整体高于没有经过特征划分的模型精度.     

MFCA的生命周期视角扩展:机理、方法与案例

可持续发展决策离不开物质流成本会计(MFCA)与生命周期评价(LCA)的整合集成,梳理文献发现当前有关MFCA生命周期视角扩展的研究尚不存在一套相对成熟的方法体系.基于约束理论,提出成本核算边界和成本核算对象是生命周期视角下MFCA扩展的逻辑起点;进一步指出,生命周期阶段的界定、全生命周期流量结构模型的构建及价值信息与非价值信息的集成是MFCA实现全生命周期扩展的核心内容.鉴于此,构建了一套包括MFCA-LCA集成流量模型和核算方法在内的MFCA生命周期扩展方法体系,并引入案例详细阐述了生命周期视角下环境损害价值核算、MFCA成本核算及MFCA-LCA综合评价的实施步骤.本研究延伸和拓展了MFCA理论,丰富了MFCA生命周期扩展的相关文献,对MFCA的实践提供了应用指引.     

企业财产台风风险评估:以浙江省台州市为例

选取企业财产作为评估对象, 利用气象数据和企业财产保险理赔数据, 在台风危险性评估和企业财产脆弱性评估的基础上, 实现了企业财产台风风险的年期望损失率计算. 以浙江省台州市企业财产台风风险评估为例, 分析了企业财产致灾的危险性指标, 应用自学习离散回归方法实现了台风强度与企业财产脆弱性关系识别. 研究结果表明: 过程降雨量是刻画台风致灾强度的最优指标; 过程降雨量与企业财产损失之间是非线性的脆弱性关系; 模型在小样本情况下比其他统计方法具有更高估算精度. 研究结果为区域台风风险管理提供了科学依据.