求解作业车间调度问题的混合帝国主义竞争算法

针对最小化最大完工时间的作业车间调度问题（JSP）,提出一种结合帝国主义竞争算法（ICA）和禁忌搜索（TS）算法的混合算法。混合算法以帝国主义竞争算法为基础,在同化操作中融入遗传算法中的杂交算子和变异算子,使算法全局搜索能力更强。为了克服帝国主义竞争算法局部搜索能力弱的缺点,引入禁忌搜索算法进一步优化同化操作后的后代。禁忌搜索算法采用混合邻域结构和新型选择策略,使得算法能够更有效地搜索邻域解。混合算法兼具全局搜索能力和局部搜索能力,通过对13个经典的Benchmark调度问题进行仿真测试,并与近年4种新型混合算法进行对比分析,实验结果表明了所提算法求解Job Shop调度问题的有效性和稳定性。     

混合流水车间调度的变邻域禁忌搜索算法

针对混合流水车间系统的最小化Makespan调度问题,提出一种基于关键路径理论的变邻域禁忌搜索算法,讨论其关键技术。在该算法中,提出基于关键路径的毗邻域概念,防止搜索算法陷入局部最优解,采用变邻域搜索策略,在无法改进解时,实现对移动毗邻域的搜索。仿真结果表明,该算法获得的调度结果优于简化禁忌搜索和启发式算法。     

约束满足混合算法求解提前/拖期Job Shop调度问题

针对提前/拖期Job Shop调度问题,建立其约束满足优化问题模型,提出了一种约束满足与禁忌搜索结合的混合算法。该算法基于约束满足思想,通过约束传播技术和启发式修复算法,得到可行调度作为禁忌搜索算法的初始解;再进行关键路径上的邻域变换,优化当前解;并采用一种全局邻域交换策略,扩大搜索空间,改善优化结果。数据实验表明了该混合算法的可行性和有效性。     

求解Job Shop调度问题的混合蚁群算法研究

为了解决单一算法求解Job Shop调度问题存在的不足，该文提出了一种混合算法，将蚁群算法用于全局搜索。针对蚁群算法易于陷入局部最优的情况，提出了一种基于关键工序的邻域搜索方法，将使用此邻域搜索方法的TS算法作为局部搜索策略。利用TS算法较强的局部搜索能力，提高了蚁群算法的优化能力，达到改善Job Shop调度问题解的质量。实验结果表明，混合算法在较短的时间内，找到了FT10、LA24、LA36等典型benchmarks问题的最优解，得到的makespan的平均值较并行遗传算法(PGA)和TSAB算法均有所提高。     

求解无等待流水调度的基于禁忌搜索的混合算法

本文提出了解决最小完工时间的无等待流水调度问题的基于禁忌搜索的混合算法。算法结合了调度规则和禁忌搜索算法的优点,首先利用调度规则构造较好的初始解,既可以加快禁忌搜索算法的收敛速度,也可以降低整个算法的运算量,使算法有更好的工程实用性;然后使用变邻域结构的禁忌搜索算法改进当前解。在保持可达性的基础上,该算法缩小了邻域规模和减少了计算时间。数值仿真实验表明,该算法是有效的。     

一类基于FSP问题Block性质的快速TS算法

为解决现有算法在求解大规模流水线调度问题（FSP）时计算时间过长的问题,从缩小邻域的角度出发,提出一种基于FSP问题Block性质的快速禁忌搜索（TS）算法．利用Block性质．算法在保证不丢失最优解的基础上．将邻域中大部分劣解排除．将搜索重点集中在邻域中“最优希望”的区域,以缩小邻域和减少计算时闻．数值仿真实验表明,该算法能在较短时间内获得大规模FSP问题的满意解．     

预制构件并行生产线资源配置与生产调度集成优化

并行生产线和特定工序生产资源共享模式可以显著改善客户满意度并节约成本.针对预制构件并行生产线资源配置与生产调度集成优化问题,基于分解策略和交替迭代优化思想,提出一种交替式混合果蝇-禁忌搜索算法(AHFOA＿TS)以最小化拖期惩罚费用.首先,通过快速启发式方法产生一较好初始解;然后,固定资源配置方案,为提高算法局部搜索能力,通过集成多种局部搜索方式,设计一种离散果蝇优化算法优化订单指派及调度方案;最后,固定订单指派及调度方案,为减少无效搜索次数,设计一种基于双层变异算子和精英劣解交叉策略的混合禁忌搜索算法以优化资源配置方案,如此两个阶段交替运行直至满足终止条件.此外,设计4种基于交替搜索框架的智能优化算法用于比较.计算结果表明, AHFOA＿TS算法能够更有效求解预制构件生产线资源配置和生产调度集成优化问题.     

基于TS的动态车辆调度问题的混合算法研究

对带时间窗的动态车辆调度问题进行分析,采用实时再优化方法进行研究,引入时间轴概念,建立动态车辆调度模型,并给出求解的混合禁忌搜索算法。该算法先用C-K节约算法求得初始解,然后用禁忌搜索进行优化,得到全局最优解。禁忌搜索算法中采用动态邻域移动方法构造候选解和动态禁忌长度选取策略设置紧急长度,提高算法的收敛速度。最后用实例证明该混合算法的可行性和有效性。     

模糊Job Shop调度中的混合搜索策略的研究

采用并行遗传算法作为全局搜索算法，提出一种混合搜索策略，用于求解模糊Job Shop调度问题．根据模糊Job Shop调度问题解的特征，提出基于关键工序的邻域选择方法，并将基于这种邻域选择方法的禁忌搜索算法作为局部搜索算法，加强了遗传算法局部搜索能力．针对13个困难benchmark问题的实验结果表明，在较短的时间内，混合搜索策略的算法得到的平均满意度比并行遗传算法提高4.67%，比TSAB算法提高5.76%．采用的禁忌搜索算法改善了遗传算法的局部搜索能力，说明提出的混合搜索策略是有效的．     

采用组合优化策略的电子侦察卫星规划方法

对电子侦察卫星任务规划问题进行了分析,建立了问题的多目标规划模型;设计了一种基于带后优化过程MOEO(Multi-objective Extremal Optimization)的多目标规划算法对模型进行求解,该算法包含MOEO主算法过程和基于禁忌搜索(TS)的后优化过程两部分:MOEO主算法中采用插入变异、模式变异及删除变异等算子对解空间进行搜索,基于Pareto最优概念的解排序确保了解在多个目标上的有效优化,精英策略避免了丢失进化过程中产生的非劣解;TS后优化过程中提出了多种邻域结构,使用各种邻域算子或算子的组合,对主算法Pareto最优解进一步优化,以得到更好的解。最后给出了仿真实例证明本文模型及算法对解决电子侦察卫星任务规划问题的有效性。     

A variable neighborhood search for minimizing single machine weighted earliness and tardiness with common due date

Although the concept of just-in-time (JIT) production systems has been proposed for over two decades, it is still important in real-world production systems. In this paper, we consider minimizing the total weighted earliness and tardiness with a restrictive common due date in a single machine environment, which has been proved as an NP-hard problem. Due to the complexity of the problem, metaheuristics, including simulated annealing, genetic algorithm, tabu search, among others, have been proposed for searching good solutions in reasonable computation times. In this paper, we propose a hybrid metaheuristic that uses tabu search within variable neighborhood search (VNS/TS). There are several distinctive features in the VNS/TS algorithm, including different ratio of the two neighborhoods, generating five points simultaneously in a neighborhood, implementation of the B/F local search, and combination of TS with VNS. By examining the 280 benchmark problem instances, the algorithm shows an excellent performance in not only the solution quality but also the computation time. The results obtained are better than those reported previously in the literature.     

A hybrid metaheuristic approach for the capacitated p-median problem

The capacitated p-median problem (CPMP) seeks to obtain the optimal location of p medians considering distances and capacities for the services to be given by each median. This paper presents an efficient hybrid metaheuristic algorithm by combining a proposed cutting-plane neighborhood structure and a tabu search metaheuristic for the CPMP. In the proposed neighborhood structure to move from the current solution to a neighbor solution, an open median is selected and closed. Then, a linear programming (LP) model is generated by relaxing binary constraints and adding new constraints. The generated LP solution is improved using cutting-plane inequalities. The solution of this strong LP is considered as a new neighbor solution. In order to select an open median to be closed, several strategies are proposed. The neighborhood structure is combined with a tabu search algorithm in the proposed approach. The parameters of the proposed hybrid algorithm are tuned using design of experiments approach. The proposed algorithm is tested on several sets of benchmark instances. The statistical analysis shows efficiency and effectiveness of the hybrid algorithm in comparison with the best approach found in the literature.     

Block approach—tabu search algorithm for single machine total weighted tardiness problem

Problem of scheduling on a single machine to minimize total weighted tardiness of jobs can be described as follows: there are n jobs to be processed, each job has an integer processing time, a weight and a due date. The objective is to minimize the total weighted tardiness of jobs. The problem belongs to the class of NP-hard problems. Some new properties of the problem associated with the blocks have been presented and discussed. These properties allow us to propose a new fast local search procedure based on a tabu search approach with a specific neighborhood which employs blocks of jobs and a compound moves technique. A compound move consists in performing several moves simultaneously in a single iteration of algorithm and allows us to accelerate the convergence to good solutions. In the algorithm, we use an idea which decreases the complexity for the search of neighborhood from O(n³) to O(n²). Additionally, the neighborhood is reduced by using some elimination criteria. The method presented in this paper is deterministic one and has not any random element, as distinct from other effective but non-deterministic methods proposed for this problem, such as tabu search of Crauwels, H. A. J., Potts, C. N., & Van Wassenhove, L. N. (1998). Local search heuristics for the single machine total weighted tardiness Scheduling Problem. INFORMS Journal on Computing, 10(3), 341–350, iterated dynasearch of Congram, R. K., Potts C. N., & Van de Velde, S. L. (2002). An iterated dynasearch algorithm for the single-machine total weighted tardiness scheduling problem. INFORMS Journal on Computing, 14(1), 52–67 and enhanced dynasearch of Grosso, A., Della Croce, F., & Tadei, R. (2004). An enhanced dynasearch neighborhood for single-machine total weighted tardiness scheduling problem. Operations Research Letters, 32, 68–72. Computational experiments on the benchmark instances from OR-Library (http://people.brunel.ac.uk/mastjjb/jeb/info.html) are presented and compared with the results yielded by the best algorithms discussed in the literature. These results show that the algorithm proposed allows us to obtain the best known results for the benchmarks in a short time. The presented properties and ideas can be applied in any local search procedures.     

带作业范围约束的岸桥调度模型及其算法设计

受电缆线坑位置与缆线长度的限制,岸桥作业只能在一定的横向移动范围之内。考虑到这一现实要求,结合岸桥作业禁止跨越与安全距离等特有约束,以最小化装卸作业的makespan为目标,构建了新的岸桥作业调度混合整数规划模型。针对问题的NP-hard特性,设计了一种混合模拟退火算法,运用启发式算法生成质量较高的初始解,结合遗传算法的变异运算生成邻域新解,增强了解的多样性,引入禁忌搜索算法的禁忌表操作,避免了循环搜索,提高了求解效率。大规模实验结果表明所建立的模型是有效的,算法的求解质量与效率明显优于标准模拟退火算法与禁忌搜索算法。当实验规模逐渐增大时,与LINGO软件相比,算法在求解效率方面的优势越来越明显。     

基于TS/VDS算法的涤纶短纤维生产调度优化

采用禁忌搜索（ＴＳ）／变深度搜索（ＶＤＳ）混合算法对涤纶短纤维生产调度优化问题进行优化．混合算法通过改变常规ＴＳ算法邻域,采用变深度搜索技术增强了算法寻优能力．某大型石化企业实际数据的实验结果表明,该算法在寻优能力和求解时间上比常规ＴＳ算法更加有效,能够在更短的时间内获得满意解,对于解决多产品多阶段连续生产调度问题具有实用价值．     

Decomposition based hybrid VNS–TS algorithm for distributed parallel factories scheduling with virtual corporation

The main purpose of this paper is to develop a decomposition based hybrid variable neighborhood search/tabu search (DVT) algorithm for multi-factory production network scheduling problem where a number of different individual factories collaborate despite their different objectives. It is assumed some of the network's factories are interested in total processing cost minimization whereas the remaining factories are interested in the production profits maximization. It is also assumed that jobs can migrate from their original factory to other factories but a transportation time is incurred. Our proposed algorithm comprises of a tabu search and a variable neighborhood search with several local search algorithms. In this hybridization, to improve the search ability of the algorithm, we make use of guiding principles with ordering of neighborhood structures by mixed integer linear programming relaxation. In the proposed algorithm, the parallel search strategy is designed for a scalar bi-objective. Multiple objectives are combined with L₁-metric technique then each sub-search procedure evolves separately until a good approximation of the Pareto-front is obtained. The non-dominated sets obtained from our algorithm and original heuristic (algorithm without ordering concept) are compared using three different indices. Furthermore, the problem is modeled as a mixed integer linear programming and solved by improved ϵ-constraint approach (IEA) with CPLEX solver. The results of comparisons between IEA and DVT algorithm showed the proposed algorithm yielded most of the solutions in the net non-dominated front.     

基于两次禁忌搜索的军事物资装运方案研究

针对当前军事物资装载与运输问题,映射建立数学模型,运用两次禁忌搜索算法自动输出较优的可行运输方案.第一次禁忌搜索用于确定较优的初始解,针对初始解,运用第二次禁忌搜索,保证在一定时间限制条件下,对运输问题进行优化求解.计算结果表明,该模型通过两次禁忌搜索算法可以得出在满足时间限制条件下的成本较小的装运方案,使用该模型可以有效提高载具的利用率,避免运力的浪费.     

一种基于禁忌搜索的时延约束组播路由算法

提出了一种使用禁忌搜索方法构造组播树的时延约束最小代价组播路由算法（TSBDMA)。该算法充分利用禁忌搜索方法中灵活的记忆功能和禁忌规则等特点,以最小时延树为初始解,并使用换边操作构造邻域集,最终求得满足条件的组播树。仿真实验结果表明本算法具有代价性能良好、可靠性高、收敛速度快、时延低的特点。     

An effective hybrid algorithm for the problem of packing circles into a larger containing circle

Simulated annealing is a powerful stochastic search method, but it still has the disadvantage of blind search. Tabu search (TS) which can prevent cycling and enhance diversification, is an adaptive strategy based on tabu list. By reasonably combining simulated annealing with TS, an effective hybrid algorithm for the problem of packing circles into a larger containing circle is presented. Based on a special neighborhood and tabu strategy, some benchmark problem instances can be well solved by the presented hybrid algorithm, and the computational results can compete with the best literature results.