Integrating decisions with advance supply information in an assemble-to-order system

We study a periodic-review assemble-to-order (ATO) system with multiple components and multiple products, in which the inventory replenishment for each component follows an independent base-stock policy and stochastic product demands are satisfied according to a First-Come-First-Served rule. We assume that the replenishment for various component suffers from lead time uncertainty. However, the decision maker has the so-called advance supply information (ASI) associated with the lead times and thus can take advantage of the information for system optimization. We propose a multistage stochastic integer program that incorporates ASI to address the joint optimization of inventory replenishment and component allocation. The optimal base-stock policy for the inventory replenishment is determined using the sample average approximation algorithm. Also, we provide a modified order-based component allocation (MOBCA) heuristic for the component allocation. We additionally consider a special case of the variable lead times where the resulting two-stage stochastic programming model can be characterized as a single-scenario case of the proposed multistage model. We carry out extensive computational studies to quantify the benefits of integrating ASI into joint optimization and to explore the possibility of employing the two-stage model as a relatively efficient approximation scheme for the multistage model.     

Inventory policies with quantized ordering

This article studies (nQ, r) inventory policies, under which the order quantity is restricted to be an integer multiple of a base lot size Q. Both Q and r are decision variables. Assuming the one-period expected holding and backorder cost function is unimodal, we develop an efficient algorithm to compute the optimal Q and r. The algorithm is facilitated by simple observations about the cost function and by tight upper bounds on the optimal Q. The total number of elementary operations required by the algorithm is linear in these upper bounds. By using the algorithm, we compare the performance of the optimal (nQ, r) policy with that of the optimal (s, S) policy through a numerical study, and our results show that the difference between them is small. Further analysis of the model shows that the cost performance of an (nQ, r) policy is insensitive to the choice of Q. These results establish that (nQ, r) models are potentially useful in many settings where quantized ordering is beneficial.     

Supply chain coordination with product line design and a revenue sharing scheme

Many manufacturers sell their products through retailers and share the revenue with those retailers. Given this phenomenon, we build a stylized model to investigate the role of revenue sharing schemes in supply chain coordination and product variety decisions. In our model, a monopolistic manufacturer serves two segments of consumers, which are distinguished by their willingness to pay for quality. In the scenario with exogenous revenue sharing ratios, when the potential gain from serving the low segment is substantial (e.g., the low‐segment consumers' willingness to pay is high enough or the low segment takes a large enough proportion of the market), the retailer is better off abandoning the revenue sharing scheme. Moreover, when the potential gain from serving the low (high) segment is substantial enough, the manufacturer finds it profitable to offer a single product. Furthermore, when revenue sharing ratios are endogenous, we divide our analysis into two cases, depending on the methods of cooperation. When revenue sharing ratios are negotiated at the very beginning, the decentralized supply chain causes further distortion. This suggests that the central premise of revenue sharing—the coordination of supply chains—may be undermined if supply chain parties meticulously bargain over it.     

Single‐machine scheduling with deadlines to minimize the total weighted late work

We consider scheduling a set of jobs with deadlines to minimize the total weighted late work on a single machine, where the late work of a job is the amount of processing of the job that is scheduled after its due date and before its deadline. This is the first study on scheduling with the late work criterion under the deadline restriction. In this paper, we show that (i) the problem is unary NP‐hard even if all the jobs have a unit weight, (ii) the problem is binary NP‐hard and admits a pseudo‐polynomial‐time algorithm and a fully polynomial‐time approximation scheme if all the jobs have a common due date, and (iii) some special cases of the problem are polynomially solvable.     

维修性增长趋势检验研究

对即时改进和延缓改进两种维修性增长规划方式进行了趋势检验研究.针对即时改进的维修性增长规划方式,提出了趋势检验的图示法和Laplace方法.针对延缓改进的维修性增长规划方式,根据修复率(第i阶段的修复率为μi)的顺序约束条件:∞>μm≥…≥μi≥…≥μ2≥μ1>0,探讨了指数分布和正态分布维修性增长趋势检验的区间估计法,并结合数值例说明了这些方法的可行性.     

基于multi-agent编组的校园虚拟实验网格任务分配策略

在网格计算环境下,许多任务的执行经常需要同时协同分配多个agent以满足性能需求.提出了一种新的基于multi-agent编组机制的agent协同分配方法.首先,对传统编组算法和multi-agent编组算法进行了分析比较.然后,设计了校园虚拟实验网格调度系统及其任务分配算法,实验结果表明:当CDR=0.2时,算法与传统算法带来最好的目标价值,在某些条件下,传统算法略微胜过该算法,当CDR增大时,该算法比传统算法执行得更好.     

小展弦比翼面颤振分析方法研究

给出了一种适用于小展弦比翼面初步设计的颤振分析方法.根据小展弦比翼面结构特征,运用简化的理想模态和活塞理论建立颤振分析模型,分析了翼面结构参数对颤振特性的影响.并以某型翼面为例验证了本方法的实用性,与NASTRAN计算结果进行了比较分析.     

认真学习贯彻胡主席重要指示精神在新的起点上推进军队党的建设

按照胡主席重要讲话精神推进军队党的建设,必须正确认识和准确把握军队党的建设新的历史起点;牢牢把握"铸牢军魂"这个根本目的;以改革的精神统筹谋划和整体推进各项建设;突出抓好党内民主建设和反腐倡廉建设。     

军队思想政治建设实现“三个确保”的路径探索

军队思想政治建设实现"三个确保",必须以强化中国特色社会主义理论体系武装为首要任务;以培育当代革命军人核心价值观为重要抓手;以全面提高完成多样化军事任务能力为实践平台;以加强各级党组织建设为关键环节;以改进创新思想政治工作为强大动力.     

重视培育军官职业精神

培育军官职业精神是建立中国特色军官职业化制度的内在要求.要准确把握我军军官职业精神的基本特点.确立培育军官职业精神的内容、方法、评价和督导体系.