产业结构优化研究

中国的工业化进程在实现数量上的高速增长和产业规模大幅扩张的同时,其增长方式、增长质量和效率已然成为新时期的重大问题,对我国产业结构优化进程的考察无疑在上述方面具有重要意义。本文在清楚辨析产业结构升级和产业结构优化的基础上,对我国“十一五”期间产业结构的优化进程进行分析。结论表明,我国产业结构具有较明显的高度化发展态势;但是产业结构合理化进程并不明显,特别是产业结构的高度化和合理化的进程并不一致,产业结构调整并没有取得“对经济发展方式转变具有促进作用”的优化效果。在通往新型工业化的道路上,经济结构调整和增长方式的转变仍然是我们亟需解决的重要问题。     

资本在西部地区科技资源配置中作用初探

科技资源是第一资源 ,对西部地区来说更是如此 ,如何充分发挥资本在科技资源配置中的作用 ,如何在有限的生产要素中有选择地进行最合理的投入 ,以使投入产出达到最大 ,本文通过数学模型的建立给出一些参考意见。     

An Extended Sequential Imperfect Preventive Maintenance Model with Improvement Factors

This article presents a generalization of the imperfect sequential preventive maintenance (PM) policy with minimal repair. As failures occur, the system experiences one of two types of failures: a Type-I failure (minor), rectified by a minimal repair; or a Type-II failure (catastrophic) that calls for an unplanned maintenance. In each maintenance period, the system is maintained following the occurrence of a Type-II failure or at age, whichever takes place first. At the Nth maintenance, the system is replaced rather than maintained. The imperfect PM model adopted in this study incorporates with improvement factors in the hazard-rate function. Taking age-dependent minimal repair costs into consideration, the objective consists of finding the optimal PM and replacement schedule that minimize the expected cost per unit time over an infinite time-horizon.     

农业结构优化对土地生产率和农业增长的影响

采用土地生产率分解法,将农业增长的决定因素分解为导致土地生产率增长的非结构优化因素和结构优化因素,利用中国1979-2006年土地生产率的数据,分别估算其对农业增长的贡献,并进一步分析影响农业结构优化对农业增长贡献相关因素,发现农户对农产品价格预期的准确性对其影响最为显著。     

法院民事调解在和谐社会构建中的功能

司法的目的是要形成和谐秩序,并非对抗态势。调解之所以受到关注和重视,关键是它在解决社会纠纷中发挥着特殊的功能。民事诉讼调解制度是和谐主义模式的诉讼机制中重要组成部分,是促进社会纠纷和谐解决的重要方式。     

浅谈企业知识型员工激励效果的优化

从知识型员工激励效果不佳的现状入手,分析了影响激励效果的因素,提出了知识型员工激励效果优化的流程和相关措施,以期帮助企业针对现有的激励机制查找激励效果不佳的原因,对症下药,收到事半功倍的效果。     

Performance Measures for Selection of Metamodels to be Used in Simulation Optimization

This paper points out the need for performance measures in the context of simulation optimization and suggests six such measures. Two of the measures are indications of absolute performance, whereas the other four are useful in assessing the relative performance of various candidate metamodels. The measures assess performance on three fronts: accuracy of placing optima in the correct location, fit to the response, and fit to the character of the surface (expressed in terms of the number of optima). Examples are given providing evidence of the measures' utility—one in a limited scenario deciding which of two competing metamodels to use as simulation optimization response surfaces vary, and the other in a scenario of a researcher developing a new, sequential optimization search procedure.     

Optimal design of supply chain networks under uncertain transient demand variations

We consider a detailed mathematical formulation for the problem of designing supply chain networks comprising multiproduct production facilities with shared production resources, warehouses, distribution centers and customer zones and operating under time varying demand uncertainty. Uncertainty is captured in terms of a number of likely scenarios possible to materialize during the lifetime of the network. The problem is formulated as a mixed-integer linear programming problem and solved to global optimality using standard branch-and-bound techniques. A case study concerned with the establishment of Europe-wide supply chain is used to illustrate the applicability and efficiency of the proposed approach. The results obtained provide a good indication of the value of having a model that takes into account the complex interactions that exist in such networks and the effect of inventory levels to the design and operation.     

Capacity rationing in rental systems with two customer classes and batch arrivals

Service differentiation is an emerging method to improve profit and to better serve high-priority customers. Such an approach has recently been introduced by one of Europe's leading rail cargo companies. Under this approach, customers can choose between classic and premium services. Premium service is priced above classic service and premium customers receive a service guarantee which classic customers do not receive. The company has to decide under which conditions it should ration its fleet capacity to classic customers in order to increase service of premium customers. We model such a situation as a batch-arrival queuing loss system. We describe the model, solve it optimally, and derive quantities of interest such as service probabilities. We further analyze it by performing numerical experiments based on the data from the company that motivated our research. We show that the potential of capacity rationing can be substantial in situations like the one we analyzed. We also derive conditions under which rationing is especially beneficial, such as under high unit fleet holding costs or in the presence of batch arrivals compared to single arrivals.     

Models and algorithms for the design of survivable multicommodity flow networks with general failure scenarios

We consider the design of a multicommodity flow network, in which point-to-point demands are routed across the network subject to link capacity restrictions. Such a design must build enough capacity and diverse routing paths through the network to ensure that feasible multicommodity flows continue to exist, even when components of the network fail. In this paper, we examine several methodologies to optimally design a minimum-cost survivable network that continues to support a multicommodity flow under any of a given set of failure scenarios, where each failure scenario consists of the simultaneous failure of multiple arcs. We begin by providing a single extensive form mixed-integer programming formulation for this problem, along with a Benders decomposition algorithm as an alternative to the extensive form approach. We next investigate strategies to improve the performance of the algorithm by augmenting the master problem with several valid inequalities such as cover constraints, connectivity constraints, and path constraints. For the smallest instances (eight nodes, 10 origin–destination pairs, and 10 failure scenarios), the Benders implementation consumes only 10% of the time required by the mixed-integer programming formulation, and our best augmentation strategy reduces the solution time by another 50%. For medium- and large-sized instances, the extensive form problem fails to terminate within 2 h on any instance, while our decomposition algorithms provide optimal solutions on all but two problem instances.