A bicriterion approach to common flow allowances due window assignment and scheduling with controllable processing times

We investigate a single‐machine scheduling problem for which both the job processing times and due windows are decision variables to be determined by the decision maker. The job processing times are controllable as a linear or convex function of the amount of a common continuously divisible resource allocated to the jobs, where the resource allocated to the jobs can be used in discrete or continuous quantities. We use the common flow allowances due window assignment method to assign due windows to the jobs. We consider two performance criteria: (i) the total weighted number of early and tardy jobs plus the weighted due window assignment cost, and (ii) the resource consumption cost. For each resource consumption function, the objective is to minimize the first criterion, while keeping the value of the second criterion no greater than a given limit. We analyze the computational complexity, devise pseudo‐polynomial dynamic programming solution algorithms, and provide fully polynomial‐time approximation schemes and an enhanced volume algorithm to find high‐quality solutions quickly for the considered problems. We conduct extensive numerical studies to assess the performance of the algorithms. The computational results show that the proposed algorithms are very efficient in finding optimal or near‐optimal solutions. © 2017 Wiley Periodicals, Inc. Naval Research Logistics, 64: 41–63, 2017     

测试性增长中资源优化配置模型及求解

良好的测试性设计对系统维修性具有重要意义,测试性增长试验通过一系列测试性设计缺陷发现和纠正措施,可保证系统测试性指标达到设计要求。针对基于延缓纠正的测试性增长过程中的资源配置问题进行研究,基于增长试验目标是否明确和试验资源是否受限制问题构建资源优化配置模型,并提出一种基于拉格朗日松弛和本地搜索的快速优化算法。仿真结果表明:该模型能够有效指导测试性增长中的资源优化配置问题,所提混合优化方法能够高效、准确地求解整数规划问题。     

军事云环境下基于动态博弈的资源调度方法

针对军事云环境下联合指挥资源调度优化问题,综合考虑了多部队任务需求,多目标优化,多部队资源竞争等约束条件,运用动态博弈理论及方法,建立并提出了一种基于完全信息扩展博弈的资源调度模型及方法,提高了资源调度效率,兼顾了多部队利益,增加了联合作战效益。最后通过实验验证了其有效性及准确性。     

A self‐adapting genetic algorithm for project scheduling under resource constraints

This papers deals with the classical resource‐constrained project scheduling problem (RCPSP). There, the activities of a project have to be scheduled subject to precedence and resource constraints. The objective is to minimize the makespan of the project. We propose a new heuristic called self‐adapting genetic algorithm to solve the RCPSP. The heuristic employs the well‐known activity list representation and considers two different decoding procedures. An additional gene in the representation determines which of the two decoding procedures is actually used to compute a schedule for an individual. This allows the genetic algorithm to adapt itself to the problem instance actually solved. That is, the genetic algorithm learns which of the alternative decoding procedures is the more successful one for this instance. In other words, not only the solution for the problem, but also the algorithm itself is subject to genetic optimization. Computational experiments show that the mechanism of self‐adaptation is capable to exploit the benefits of both decoding procedures. Moreover, the tests show that the proposed heuristic is among the best ones currently available for the RCPSP. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 433–448, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10029     

使用平均周期进行指纹分类

提出了一种基于指纹平均周期的分类方法,通过计算指纹的平均周期并按照平均周期将数据库中的指纹进行排序,该方法可有效地提高指纹的搜索速度。若将基于指纹周期的分类算法和现有的指纹分类算法结合起来,则可进一步提高指纹搜索效率。     

An efficient metaheuristic for integrated scheduling and staffing IT projects based on a generalized minimum cost flow network

Scheduling IT projects and assigning the project work to human resources are an important and common tasks in almost any IT service company. It is particularly complex because human resources usually have multiple skills. Up to now only little work has considered IT‐specific properties of the project structure and human resources. In this article, we present an optimization model that simultaneously schedules the activities of multiple IT projects with serial network structures and assigns the project work to multiskilled internal and external human resources with different efficiencies. The goal is to minimize costs. We introduce a metaheuristic that decomposes the problem into a binary scheduling problem and a continuous staffing problem where the latter is solved efficiently by exploiting its underlying network structure. For comparison, we solve the mixed–binary linear program with a state–of–the–art commercial solver. The impacts of problem parameters on computation time and solution gaps between the metaheuristic and the solver are assessed in an experimental study. Our results show that the metaheuristic provides very favorable results in considerable less time than the solver for midsize problems. For larger problems, it shows a similar performance while the solver fails to return feasible solutions. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 59: 111–127, 2012     

基于时间窗的宽带阵列多目标干扰资源调度

随着宽带数字阵列技术和有源干扰技术的不断发展和成熟,舰载有源干扰设备的未来发展方向将是宽带数字阵列有源干扰系统。针对多目标干扰问题,提出了目标干扰时间窗概念和两种时间窗的处理方法,并建立干扰资源调度模型,通过仿真计算和对比分析,得出基于模糊时间窗的资源调度模型性能优于基于硬时间窗的资源调度模型,能够对干扰资源进行合理的调度,提高宽带阵列多目标干扰能力。     

Inspection games with local and global allocation bounds

This article discusses a two‐player noncooperative nonzero‐sum inspection game. There are multiple sites that are subject to potential inspection by the first player (an inspector). The second player (potentially a violator) has to choose a vector of violation probabilities over the sites, so that the sum of these probabilities do not exceed one. An efficient method is introduced to compute all Nash equilibria parametrically in the amount of resource that is available to the inspector. Sensitivity analysis reveals nonmonotonicity of the equilibrium utility of the inspector, considered as a function of the amount of resource that is available to it; a phenomenon which is a variant of the well‐known Braess paradox. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

多平台雷达有源干扰资源分配算法

根据现代干扰机特点,建立"多对多"雷达有源干扰资源分配数学模型,结合分配算法的具体应用环境,提出了基于多Agent分布协同拍卖的雷达干扰资源分配算法,实例表明该方法可行。     

基于灰色局势决策的通用维修资源整合方法

维修资源是装备保障系统的重要组成部分,针对部队装备维修资源品种越来越多、保障负担越来越重的问题,分析了通用维修资源的优点,提出了一种基于灰色局势决策理论的通用维修资源整合方法,并给出了具体实施步骤,主要包括构建决策目标体系、制定决策流程、计算综合测度和选择决策等,最后还进行了详细的案例研究.为维修资源的有效整合提供了决策依据和科学方法,对于减少维修资源种类、提高装备保障效率具有一定的指导作用和应用价值.