The value of information sharing in a two‐stage supply chain with production capacity constraints

We consider a simple two‐stage supply chain with a single retailer facing i.i.d. demand and a single manufacturer with finite production capacity. We analyze the value of information sharing between the retailer and the manufacturer over a finite time horizon. In our model, the manufacturer receives demand information from the retailer even during time periods in which the retailer does not order. To analyze the impact of information sharing, we consider the following three strategies: (1) the retailer does not share demand information with the manufacturer; (2) the retailer does share demand information with the manufacturer and the manufacturer uses the optimal policy to schedule production; (3) the retailer shares demand information with the manufacturer and the manufacturer uses a greedy policy to schedule production. These strategies allow us to study the impact of information sharing on the manufacturer as a function of the production capacity, and the frequency and timing in which demand information is shared. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

基于未确知测度的多目标决策方法及其应用

定义策略、目标和评判三个空间以及满足非负性、归一性和可加性的未确知测度函数,给出了适合于有序分割类评判空间寻优的最优决策准则,从而提出了一种未确知信息数学处理理论基础上的未确知测度决策方法,对含多因素特别是难以量化因素的决策问题寻优建立了一个合理、精细、分辨率高、计算简单高效的数学模型,用来求解多目标决策问题中的最优策略,并结合火力打击选择的一个实例分析,获得了较为成功的应用.     

ATIE:一种自适应的可调域间出口选择算法

TIE算法能对域间出口的选择进行调节,但是该算法的参数计算过于复杂,并且出口选择的调节并不能随负载的变化而变化,因此提出了一种自适应的可调域间出口选择算法ATIE,该算法能够满足流量工程和网络健壮性要求,并通过参数T的改变随当前负载的变化而变化.实验表明,ATIE算法能够在控制剖面敏感性和随负载变化的流量工程自适应性上达到合理的折衷.     

舰船最优概念设计方案的构造方法研究

在舰船概念设计阶段,设计者往往需要从大量设计方案中筛选优秀方案,此问题属于多属性多目标优化的问题,而进化算法的兴起为此类问题的解决提供了较好的途径.针对进化算法中Pareto最优解集的特点,结合舰船设计实际,提出一种新的构造最优解集的方法--提取法.案例验证表明,提取法是合理和有效的.     

Modeling and analysis of multiobjective lot splitting for N‐product M‐machine flowshop lines

Lot splitting is a new approach for improving productivity by dividing production lots into sublots. This approach enables accelerating production flow, reducing lead‐time and increasing the utilization of organization resources. Most of the lot splitting models in the literature have addressed a single objective problem, usually the makespan or flowtime objectives. Simultaneous minimization of these two objectives has rarely been addressed in the literature despite of its high relevancy to most industrial environments. This work aims at solving a multiobjective lot splitting problem for multiple products in a flowshop environment. Tight mixed‐integer linear programming (MILP) formulations for minimizing the makespan and flowtime are presented. Then, the MinMax solution, which takes both objectives into consideration, is defined and suggested as an alternative objective. By solving the MILP model, it was found that minimizing one objective results in an average loss of about 15% in the other objective. The MinMax solution, on the other hand, results in an average loss of 4.6% from the furthest objective and 2.5% from the closest objective. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

A note on combined job selection and sequencing problems

We investigate the solvability of two single‐machine scheduling problems when the objective is to identify among all job subsets with cardinality k,1≤k≤n, the one that has the minimum objective function value. For the single‐machine minimum maximum lateness problem, we conclude that the problem is solvable in O(n²) time using the proposed REMOVE algorithm. This algorithm can also be used as an alternative to Moore's algorithm to solve the minimum number of tardy jobs problem by actually solving the hierarchical problem in which the objective is to minimize the maximum lateness subject to the minimum number of tardy jobs. We then show that the REMOVE algorithm cannot be used to solve the general case of the single‐machine total‐weighted completion time problem; we derive sufficient conditions among the job parameters so that the total weighted completion time problem becomes solvable in O(n²) time. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 449–453, 2013     

非周期不完全检测下的维修优化

针对gamma退化型单部件系统,基于更新和半更新过程理论建立了以期望费用率最小为目标的非周期不完全检测下的维修优化模型。利用检测规划函数使系统的检测间隔期可以依据系统的状态进行调整。为更加贴近实际,模型考虑了测量误差对维修优化的影响。通过计算可以得到最优预防性维修阈值和检测方案。给出了模型的应用算例,通过对退化速率和费用参数的灵敏度分析说明了模型的有效性。与不考虑检测误差的优化结果进行对比,证明了考虑检测误差的重要性。     

舰载火箭炮子母弹射击火力分配模型

摘 要：由于舰载火箭弹的弹道特性与普通身管炮弹有着明显的差异,传统的舰炮射击效力计算及火力分配方法不适用于舰载火箭炮。结合舰载火箭弹弹道特点,分析了其射击误差,探讨了集群目标的简化处理方法,提出了一种基于蒙特卡洛法的舰载火箭炮对岸射击最优效力射火力分配计算模型。通过举例分析表明,该方法切实可行,利用该模型可以提高射击指挥员指挥决策的科学性。     

面向多最优解组合优化问题的决策求解算法

针对具有固定物品总和、多最优解特征的组合优化问题,以固定总和实数子集问题和购买鸡翅问题为例,给出了这类多最优解组合优化问题的形式化表示。在分析枚举等经典算法基础上,提出了基于整数状态表示和实数状态表示的0-1决策递归搜索多最优解动态规划算法。针对该算法在最优解数量较大时,时间复杂度趋向O(mⁿ)的问题,提出了基于相同决策路径合并和基于0-x决策的两种改进算法。实验中两种改进算法的计算时间基本符合与O(nb+nm)的正比关系,表明对于这类多最优解组合优化问题具有良好的求解性能。     

Interval scheduling: A survey

In interval scheduling, not only the processing times of the jobs but also their starting times are given. This article surveys the area of interval scheduling and presents proofs of results that have been known within the community for some time. We first review the complexity and approximability of different variants of interval scheduling problems. Next, we motivate the relevance of interval scheduling problems by providing an overview of applications that have appeared in literature. Finally, we focus on algorithmic results for two important variants of interval scheduling problems. In one variant we deal with nonidentical machines: instead of each machine being continuously available, there is a given interval for each machine in which it is available. In another variant, the machines are continuously available but they are ordered, and each job has a given “maximal” machine on which it can be processed. We investigate the complexity of these problems and describe algorithms for their solution. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007