Scheduling a production–distribution system to optimize the tradeoff between delivery tardiness and distribution cost

We consider a make‐to‐order production–distribution system with one supplier and one or more customers. A set of orders with due dates needs to be processed by the supplier and delivered to the customers upon completion. The supplier can process one order at a time without preemption. Each customer is at a distinct location and only orders from the same customer can be batched together for delivery. Each delivery shipment has a capacity limit and incurs a distribution cost. The problem is to find a joint schedule of order processing at the supplier and order delivery from the supplier to the customers that optimizes an objective function involving the maximum delivery tardiness and the total distribution cost. We first study the solvability of various cases of the problem by either providing an efficient algorithm or proving the intractability of the problem. We then develop a fast heuristic for the general problem. We show that the heuristic is asymptotically optimal as the number of orders goes to infinity. We also evaluate the performance of the heuristic computationally by using lower bounds obtained by a column generation approach. Our results indicate that the heuristic is capable of generating near optimal solutions quickly. Finally, we study the value of production–distribution integration by comparing our integrated approach with two sequential approaches where scheduling decisions for order processing are made first, followed by order delivery decisions, with no or only partial integration of the two decisions. We show that in many cases, the integrated approach performs significantly better than the sequential approaches. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

基于多目标模糊决策模型的联合作战方案优选

为选择作战方案中的最优方案,对所有的方案进行了排序,依据定性准则和定量的数学模型,利用多目标模糊决策分析方法,对联合作战方案的相关因素进行了分析,综合评价出各方案的优劣程度,最后得到了较为合理的作战方案先后顺序.     

一种新型内曲线式径向柱塞泵的设计

讨论了各种液压泵的使用特点,提出了一种新型内曲线式径向柱塞泵的设计思路.通过合理设计泵内定子内曲线表面,在理论上实现了无流量脉动;为了提高柱塞泵的使用寿命,采取了降低定子导轨压力角的措施;通过Matlab实现了定子表面曲线和压力角的仿真计算;理论分析的结果对于设计和制造低噪声的柱塞式液压泵有一定的指导意义.     

红河州边境地区治安问题探析

云南省红河州中越边境地区治安问题十分突出,直接影响着边境经济社会稳定。解决这一问题需要创新理念,建立高效规范的边境管理体系;加强警务合作,开展专项整治,保持高压态势打击边境地区各类违法犯罪活动;加强信息交流,发挥情报侦查在管控边境上的主导作用;加强边境联合执法,建立健全科学管控联动机制;加大经费投入,坚持科技强警思想,全面加强边防派出所执法队伍建设。     

Scheduling with centralized and decentralized batching policies in concurrent open shops

This article considers batch scheduling with centralized and decentralized decisions. The context of our study is concurrent open shop scheduling where the jobs are to be processed on a set of independent dedicated machines, which process designated operations of the jobs in batches. The batching policy across the machines can be centralized or decentralized. We study such scheduling problems with the objectives of minimizing the maximum lateness, weighted number of tardy jobs, and total weighted completion time, when the job sequence is determined in advance. We present polynomial time dynamic programming algorithms for some cases of these problems and pseudo‐polynomial time algorithms for some problems that are NP‐hard in the ordinary sense. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 58: 17–27, 2011     

基于模糊综合决策的军事信息网络效能评估

为了解决复杂战场环境下军事信息网络效能分析中存在的模糊性和不确定性,将模糊综合评判理论应用于军事信息网络。在介绍模糊综合评判决策模型和评估理论基础上,提出了军事信息网络效能评估指标体系,并通过实例仿真验证了使用方法的有效性和可行性。     

基于模糊综合评价的再制造发动机抽样方案决策研究

影响因素难以量化是再制造发动机抽样方案选择过程中的难点,不可避免地给检验人员带来了主观性和片面性的问题。提出了应用模糊综合评价方法的解决方案,建立了再制造发动机抽样方案综合评价指标体系,详细阐述了综合评价方法的算法步骤,最后以某再制造发动机抽样方案的决策为例进行了实例应用。模糊综合评价方法解决了再制造发动机抽样方案选择中所遇到的问题,可为检验人员选择合理的抽样方案提供决策支持。     

基于排放和模糊神经网络模型的柴油机故障诊断方法

根据排放检测数据规律,定义并提取特征参数,建立了规则与模糊神经网络有机结合的柴油机故障诊断模型及其对应的特征知识库,确立了模型的“可塑性”学习路线,并以单缸失火故障为例,进行了模型诊断实例研究。结果表明：运用该方法进行柴油机的故障诊断,结果准确,识别速度快,诊断效率高。     

Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times

We study a stochastic outpatient appointment scheduling problem (SOASP) in which we need to design a schedule and an adaptive rescheduling (i.e., resequencing or declining) policy for a set of patients. Each patient has a known type and associated probability distributions of random service duration and random arrival time. Finding a provably optimal solution to this problem requires solving a multistage stochastic mixed‐integer program (MSMIP) with a schedule optimization problem solved at each stage, determining the optimal rescheduling policy over the various random service durations and arrival times. In recognition that this MSMIP is intractable, we first consider a two‐stage model (TSM) that relaxes the nonanticipativity constraints of MSMIP and so yields a lower bound. Second, we derive a set of valid inequalities to strengthen and improve the solvability of the TSM formulation. Third, we obtain an upper bound for the MSMIP by solving the TSM under the feasible (and easily implementable) appointment order (AO) policy, which requires that patients are served in the order of their scheduled appointments, independent of their actual arrival times. Fourth, we propose a Monte Carlo approach to evaluate the relative gap between the MSMIP upper and lower bounds. Finally, in a series of numerical experiments, we show that these two bounds are very close in a wide range of SOASP instances, demonstrating the near‐optimality of the AO policy. We also identify parameter settings that result in a large gap in between these two bounds. Accordingly, we propose an alternative policy based on neighbor‐swapping. We demonstrate that this alternative policy leads to a much tighter upper bound and significantly shrinks the gap.     

A Fuzzy Cluster and Retinex Theory-based Variation Model for Inhomogenous Image Segmentation

A variational inhomogeneous image segmentation model based on fuzzy membership functions and Retinex theory is proposed by introducing the fuzzy membership function.The existence of the solution of the proposed model is proved theoretically.A valid algorithm is designed to make numerical solution of the model under the framework of alternating minimization.The last experimental results show that the model can make segmentation of the real image with intensity inhomogeneity effectively.