基于多目标问题的装备维修保障资源调度研究

针对战时装备维修保障资源调度面临维修保障资源需求量不确定、调度时间不确定、调度路径可靠性不确定的问题,通过引入三角模糊数,将不确定信息量化,构建了以维修保障资源调度时间最短、维修保障资源调度路径可靠性最高和维修保障资源调度成本最小为目标的多目标调度模型,并给出了确定各目标相对重要度的方法,然后通过极大极小法将多目标模型转换为单目标模型,并结合LINGO软件对模型进行求解得出维修保障资源的最优调度方案。最后,引入算例进行了分析计算,结果证明了该模型的有效性,对于战时开展装备维修保障资源调度具有一定参考价值。     

基于SAA的最小完工时间多工序并行调度研究

给出一种使用模拟退火算法(SSA)求解一类多机、多工序最小完工时间并行调度问题的方案,详细地讨论了该方案涉及的各种问题,包括目标函数和初解的确定,新解的产生方法,"温度"的更新方式及算法终止条件的确定等.文章的最后给出了该方案的一个实例和若干性能分析.     

基于约束满足的多目标对地观测卫星成像调度

EOS(对地观测卫星)成像调度需要根据用户提出的成像任务需求确定卫星成像序列,是一个复杂的组合优化问题。考虑到成像侧视约束条件,建立EOS成像调度的多目标有向无环约束图模型。在此模型的基础上提出了基于SPEA2(strength pareto evolutionary algorithm 2)的多目标成像调度算法,采用约束控制技术设计遗传算子处理成像约束。经过三个实际的多目标成像调度问题测试,表明该算法可以有效地解决EOS成像调度问题。     

面向多星观测调度的分层迭代算法

提出一种基于分治策略的多星观测分层调度框架,在该框架下,用蚁群优化算法把任务分配至各轨道圈次上,并利用自适应模拟退火算法求解各轨道圈次的调度问题。根据各轨道圈次调度结果的反馈情况,再调整任务分配方案,重复上述过程直到达到算法终止条件。为了提高算法的性能,在设计蚁群算法的启发式信息模型时,应充分考虑卫星调度问题的领域知识;在模拟退火算法中设计两个邻域结构,采用动态选择策略在优化过程中确定最佳邻域搜索结构。仿真实验表明,该方法有效地降低了问题求解的复杂度,尤其在求解大规模多星观测调度问题时表现出优异的性能。     

嵌入式操作系统多策略调度模型

分析了目前嵌入式操作系统调度策略的现状,指出了传统调度方法的不足之处,给出了多策略调度模型,该模型根据进程的属性参数决定采用哪种调度算法。多策略调度模型采用两级调度方案,即在原传统调度方法的基础上增加一级调度。一级调度确定多个调度算法的优先顺序;二级调度确定同一种调度算法中,的进程优先顺序。该模型使进程调度更加灵活和高效,应用范围更广。     

临近空间浮空器区域覆盖布局优化问题

以最大化覆盖收益和最小化覆盖代价为优化目标,建立了多浮空器区域覆盖布局优化问题的多目标混合整数规划模型,设计实现了多浮空器联合覆盖进化算法,充分利用目标位置、浮空器覆盖能力等启发式信息构造初始种群,避免进化太慢;交叉、变异算子在保证有效解的前提下,避免了算法陷入局部最优;精英策略避免丢失进化过程产生的非劣解,加快算法收...     

资源不确定军事任务计划预测调度模型与算法

针对军事任务计划执行环境中普遍存在的资源不确定性,提出了基于资源缓冲区的军事任务计划预测调度算法。算法首先基于平台有效资源功能向量进行任务—平台分配,分配过程中通过调节平台有效资源功能向量,获得不同的平台资源缓冲区分配方案;然后基于NSGA-Ⅱ算法框架对军事任务计划进行多目标求解,进而获得问题的Pareto最优解集。文章通过仿真算例对算法的可行性和有效性进行验证,实验结果表明,该算法能够有效求解资源不确定军事任务计划问题。     

基于CHARTER机制的减灾卫星调度问题研究

针对CHARTER机制下的减灾卫星(主要为成像卫星)调度问题进行了研究,介绍了CHARTER机制的工作流程,指出CHARTER机制下的减灾卫星调度实质上是一个针对区域目标的重调度问题。在此基础上提出一种改进的区域目标划分算法,并提出基于启发式规则的动态卫星重调度算法,最后通过应用实例证明了所提算法的正确性和有效性。     

空域频域不确定条件下电磁探测卫星规划方法研究

电磁探测卫星对区域目标的覆盖搜索在反恐及海上搜救等领域发挥着重要作用.针对电磁探测卫星区域搜索任务中存在的空域频域不确定性,构建了电磁探测卫星区域搜索问题(EDSASP)中不确定因素的量化描述模型及决策要素模型,提出了基于贝叶斯决策的电磁卫星任务规划方法,并以信息探测收益和前端截获收益为优化目标,建立了空域频域不确定条...     

电子侦察卫星联合侦察的混合调度算法

针对电子侦察卫星的使用约束,及不同任务的调度需求,建立了电子侦察卫星联合侦察的多目标混合整数规划模型.利用进化算法的全局搜索能力和变邻域搜索的局部优化能力,提出了一种多目标进化算法和变邻域搜索相结合两阶段混合调度算法MOEA VNS.针对问题多时间窗组合优化特点,设计了进化算子与邻域移动算子,在确保解多样性的同时使算法...     

Optimization of schedule stability and efficiency under processing time variability and random machine breakdowns in a job shop environment

The ability to cope with uncertainty in dynamic scheduling environments is becoming an increasingly important issue. In such environments, any disruption in the production schedule will translate into a disturbance of the plans for several external activities as well. Hence, from a practical point of view, deviations between the planned and realized schedules are to be avoided as much as possible. The term stability refers to this concern. We propose a proactive approach to generate efficient and stable schedules for a job shop subject to processing time variability and random machine breakdowns. In our approach, efficiency is measured by the makespan, and the stability measure is the sum of the variances of the realized completion times. Because the calculation of the original measure is mathematically intractable, we develop a surrogate stability measure. The version of the problem with the surrogate stability measure is proven to be NP‐hard, even without machine breakdowns; a branch‐and‐bound algorithm is developed for this problem variant. A tabu search algorithm is proposed to handle larger instances of the problem with machine breakdowns. The results of extensive computational experiments indicate that the proposed algorithms are quite promising in performance. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Scheduling patients in an ambulatory surgical center

This paper presents a deterministic approach to schedule patients in an ambulatory surgical center (ASC) such that the number of postanesthesia care unit nurses at the center is minimized. We formulate the patient scheduling problem as new variants of the no‐wait, two‐stage process shop scheduling problem and present computational complexity results for the new scheduling models. Also, we develop a tabu search‐based heuristic algorithm to solve the patient scheduling problem. Our algorithm is shown to be very effective in finding near optimal schedules on a set of real data from a university hospital's ASC. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

绕月轨道阴影区域建模与轨道优化

针对绕月运行轨道建立月球阴影区域与地球阴影区域的数学模型,给出了卫星是否处于阴影区域的判据;利用黄金分割法搜索出了阴影区域的边界值。将禁忌搜索算法嵌入遗传算法中并结合具体案例,搜索出了阴影时长最短的最优目标轨道。所给出的绕月轨道阴影区域模型简单且能够满足工程精度需求,可用于星上自主预报算法;所给出的嵌入式遗传算法能有效避免陷入局部最优并快速收敛。     

基于禁忌退火算法的巡航导弹航迹规划

针对巡航导弹航迹规划这个复杂的优化问题,一个禁忌退火混合优化算法被提出.首先,该算法是以基本模拟退火算法为基础.其次,为了加快该模拟退火算法的收敛速度,在恶化解的接受判断过程中,增加了一定动态的约束条件.最后,为了使最优解能够跳出局部最优的陷阱,使用了一个动态的禁忌表.仿真结果验证了该禁忌退火混合优化算法能够取得目标函数更优的航迹规划路径,从而有效提高巡航导弹的作战效能.     

Using hybrid metaheuristics for the one‐way and two‐way network design problem

A network with traffic between nodes is known. The links of the network can be designed either as two‐way links or as one‐way links in either direction. The problem is to find the best configuration of the network which minimizes total travel time for all users. Branch and bound optimal algorithms are practical only for small networks (up to 15 nodes). Effective simulated annealing and genetic algorithms are proposed for the solution of larger problems. Both the simulated annealing and the genetic algorithms propose innovative approaches. These innovative ideas can be used in the implementation of these heuristic algorithms for other problems as well. Additional tabu search iterations are applied on the best results obtained by these two procedures. The special genetic algorithm was found to be the best for solving a set of test problems. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 449–463, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10026     

A non-myopic scheduling method of radar sensors for maneuvering target tracking and radiation control

In decades, the battlefield environment is becoming more and more complex with plenty of electronic equipments. Thus, in order to improve the survivability of radar sensors and satisfy the requirement of maneuvering target tracking with a low probability of intercept, a non-myopic scheduling is proposed to minimize the radiation cost with tracking accuracy constraint. At first, the scheduling problem is formulated as a partially observable Markov decision process (POMDP). Then the tracking accuracy and radiation cost over the future finite time horizon are predicted by the posterior carmér-rao lower bound (PCRLB) and the hidden Markov model filter, respectively. Finally, the proposed scheduling is implemented efficiently by utilizing the branch and bound (B&B) pruning algorithm. Simulation results show that the performance of maneuvering target tracking was improved by the improved interacting multiple model (IMM), and the scheduler time and maximum memory consumption were significant reduced by the present B&B pruning algorithm without losing the optimal solution.     

考虑随机回放的卫星数传调度问题的一种求解方法

针对考虑随机回放的卫星数传调度问题,从置换空间到调度解空间的映射方法和置换空间的搜索算法两方面进行了研究.提出了一种时间窗优先的置换序列映射算法,并证明该映射算法可以将置换序列映射到调度解空间上的最优解.提出了一种遗传随机搜索算法,基于有记忆功能的随机邻域搜索,在置换空间上搜索产生优化调度的置换序列.仿真计算表明,遗传随机搜索算法可以增强遗传算法的局部搜索能力,在搜索结果上平均获得了2.72%的改进.     

Models and algorithms for shuffling problems in steel plants

In this article, we study item shuffling (IS) problems arising in the logistics system of steel production. An IS problem here is to optimize shuffling operations needed in retrieving a sequence of steel items from a warehouse served by a crane. There are two types of such problems, plate shuffling problems (PSP) and coil shuffling problems (CSP), considering the item shapes. The PSP is modeled as a container storage location assignment problem. For CSP, a novel linear integer programming model is formulated considering the practical stacking and shuffling features. Several valid inequalities are constructed to accelerate the solving of the models. Some properties of optimal solutions of PSP and CSP are also derived. Because of the strong NP‐hardness of the problems, we consider some special cases of them and propose polynomial time algorithms to obtain optimal solutions for these cases. A greedy heuristic is proposed to solve the general problems and its worst‐case performances on both PSP and CSP are analyzed. A tabu search (TS) method with a tabu list of variable length is proposed to further improve the heuristic solutions. Without considering the crane traveling distance, we then construct a rolling variable horizon heuristic for the problems. Numerical experiments show that the proposed heuristic algorithms and the TS method are effective. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Crane scheduling with spatial constraints

In this work, we examine port crane scheduling with spatial and separation constraints. Although common to most port operations, these constraints have not been previously studied. We assume that cranes cannot cross, there is a minimum distance between cranes and jobs cannot be done simultaneously. The objective is to find a crane‐to‐job matching which maximizes throughput under these constraints. We provide dynamic programming algorithms, a probabilistic tabu search, and a squeaky wheel optimization heuristic for solution. Experiments show the heuristics perform well compared with optimal solutions obtained by CPLEX for small scale instances where a squeaky wheel optimization with local search approach gives good results within short times. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.