基于改进遗传算法的多机调度问题

遗传算法是解决多机调度组合优化问题最有效的方法之一,但由于其自身存在着一定的缺陷应用受到一定的限制.针对遗传算法的“早熟”和非均匀地在优化空间中搜索等缺陷,提出了一种自适应选择交叉概率、变异概率以及交叉位置非等概率选取的改进的遗传算法,并将其用于某钢管钢绳企业的多机调度问题,进行了仿真分析.     

并行多机调度问题的一种遗传算法

运用遗传算法对最小化完工时间的并行多机调度问题进行了研究，给出了最小完工时间的一个下界，由此提出了初始种群的一种构造方法，并用计算实例表明该方法适用于大规模并行多机调度问题     

作业车间调度问题的改进混合遗传算法

作业车间调度是一类求解困难的组合优化问题,本文在考虑遗传算法早熟收敛问题和禁忌搜索法自适应优点的基础上,将遗传算法和禁忌搜索法相结合,提出了一种基于遗传和禁忌搜索的混合算法,并用实例对该算法进行了仿真研究.结果表明,该算法有很好的收敛精度,是可行的,与传统的算法相比较,有明显的优越性.     

考虑释放时间的单机JIT调度问题

本文主要研究二级供应链中的生产-库存-直接配送协同调度问题,其中存在一个制造商和多个零售商, 制造商根据订单进行生产, 然后将产品配送给零售商。该类问题可以抽象为考虑释放时间的单机JIT调度问题。借助于禁忌搜索算法, 本文提出了求解问题的CTA-TS算法, 并通过大量的实验数据与已有算法进行比较,说明了本文提出算法的有效性。     

多车场有时间窗的多车型车辆调度及其禁忌算法研究

本文针对物流配送中的多车场车辆调度问题提出了两种多车场的处理方法，介绍了多车场车辆调度问题中容量、时间窗、多车型等多种约束的处理方法，并且根据具体约束情况设计了禁忌算法，对多车场有时间窗的多车型车辆调度问题加以实现，给出了一个具有代表性的算例试验结果和结果分析，通过试验表明了此方法对优化有时间窗的多车型车辆调度问题的有效性．     

改进回溯搜索算法求解多目标柔性作业车间调度问题

随着绿色制造的到来,在调度问题中考虑能源消耗相关的目标变得至关重要,这已经成为了当下热点研究领域。因此,本文建立以最小化最大完工时间、机器总负荷和总能量消耗为目标的柔性作业车间调度数学模型。就回溯搜索算法的缺点提出改进,该算法通过结合改变个体搜索幅度因子对变异操作进行动态控制,防止种群迭代过程中陷入局部最优,然后通过结合个体引导与随机数扰乱提出一种新的交叉算子,提高后期寻优能力,防止了算法过早收敛。最后,运用基准算例对该算法的求解性进行了验证,并与文献中其他算法从求解精度、求解多样性、求解最优值等方面进行对比,结果表明该改进算法具有优越的求解性能。最后为该问题后续研究提供了三个可行方向：考虑更多约束条件、增加局部搜索算子和考虑实例分析。     

基于前摄性调度的电动汽车路径问题研究

针对车辆调度过程中资源不均衡的问题,利用需求的不确定性,将配送周期划分为初始配送阶段和补货阶段,建立多阶段电动汽车的两级车辆路径优化模型.根据需求的动态程度对配送区域进行划分,结合前摄性调度和反应性调度策略,提出了一种混合禁忌搜索算法(HTSA)来求解该模型.在真实的案例和多个基准评估算例上的实验结果表明:模型和算法的性能优于传统的启发式算法,具有一定的实用价值.     

多重运输调度问题的表搜索算法

本文提出了多重运输调度问题的表搜索算法，实际运算表明，这些算法具有较快的收敛速度，为解决实际问题提供了一条有效的途径。     

集装箱码头桥机调度问题基于完工时间下界的算法

关注单船桥机调度问题,指出了单船桥机的闲置会影响码头整体的运作效率。以单个集装箱为任务单位,考虑桥机移动时间、安全距离等约束,建立了最小化桥机完工时间和闲置时间的多目标规划模型。基于完工时间下界的两种不同情况：以重点贝位工作量确定和以平均工作量确定,分别设计了基于邻域搜索的启发式算法和基于贪心策略的“分割贝位”算法,并且证明了在以平均工作量确定下界的情况中该算法不会导致桥机闲置。不同规模、不同下界类型的算例表明：提出的模型与算法得到的桥机调度计划更适合实际生产作业,能够有效地逼近完工时间下界,算法运行速度较现有的研究有显著的提高。     

考虑成本的最大延迟时间同类机调度问题

假定生产时机器成本是固定的,研究了一类考虑成本的同类机调度问题,调度的目标是在给定加工完所有作业的总预算的成本限制下最小化最大作业延迟时间。为该类问题构建了混合整数规划模型。通过设计相关规则在机器成本预算内来选择加工机器,以及对传统的LPT(最长加工时间优先)、ECT(最早完工时间优先)、EDD(最早工期优先)等算法进行改进,提出了一个启发式算法H,并理论证明了该算法在同型机和同类机下的最坏误差界。通过算例说明了算法的执行情况,同时也考虑了给定总预算不同的多种情形,采用大量随机数据实验验证了算法的有效性。     

Heuristic Techniques for Single Line Train Scheduling

Optimising a train schedule on a single line track is known to be NP-Hard with respect to the number of conflicts in the schedule. This makes it difficult to determine optimum solutions to real life problems in reasonable time and raises the need for good heuristic techniques. The heuristics applied and compared in this paper are a local search heuristic with an improved neighbourhood structure, genetic algorithms, tabu search and two hybrid algorithms. When no time constraints are enforced on solution time, the genetic and hybrid algorithms were within five percent of the optimal solution for at least ninety percent of the test problems.     

基于低碳排放的车辆路径优化问题研究

研究了基于低碳排放的锦州JS配送公司的车辆路径优化问题.首先通过分析目前锦州JS配送公司的车辆路径规划方案发现该公司在规划路径时只关注路径最短,而忽视了碳排放成本.然后通过具体分析配送过程中能源消耗的来源,考虑车辆自重和载重、车辆出行距离等对配送能源消耗的影响,建立了以极小化碳排放成本为目标的车辆路径优化问题的混合整数规划模型,通过求解模型得到新的配送路径优化方案.优化后的配送方案比原先的配送方案减少了14.16万元的碳排放成本.研究结果对物流企业降低碳排放具有指导意义.     

A Tabu Search Heuristic for a Full-Load, Multi-Terminal, Vehicle Scheduling Problem with Backhauling and Time Windows

The problem considered is the full-load pickup and delivery problem with time windows (PDPTW), and heterogeneous products and vehicles, where the assignment of pickup points to requests is not predetermined. Elements associated with tabu search, such as diversification by reversion to junctions and the use of soft aspiration criteria, are embedded into our tabu search implementation. This metaheuristic is evaluated using random instances and selected data from a construction company in the U.K. The obtained results are compared against lower bounds from LP relaxation and also solutions from an existing multi-level heuristic.     

Design and Evaluation of Tabu Search Algorithms for Multiprocessor Scheduling

Using a simple multiprocessor scheduling problem as a vehicle, we explore the behavior of tabu search algorithms using different tabu, local search and list management strategies. We found that random blocking of the tail of the tabu list always improved performance; but that the use of frequency-based penalties to discourage frequently selected moves did not. Hash coding without conflict resolution was an effective way to represent solutions on the tabu list. We also found that the most effective length of the tabu list depended on features of the algorithm being used, but not on the size and complexity of the problem being solved. The best combination of features included random blocking of the tabu list, tasks as tabus and a greedy local search. An algorithm using these features was found to outperform a recently published algorithm solving a similar problem.     

An Optimization Based Approach to the Train Operator Scheduling Problem at Singapore MRT

Singapore Mass Rapid Transit (SMRT) operates two train lines with 83 kilometers of track and 48 stations. A total of 77 trains are in operation during peak hours and 41 during off-peak hours. In this article we report on an optimization based approach to develop a computerized train-operator scheduling system that has been implemented at SMRT. The approach involves a bipartite matching algorithm for the generation of night duties and a tabu search algorithm for the generation of day duties. The system automates the train-operator scheduling process at SMRT and produces favorable schedules in comparison with the manual process. It is also able to handle the multiple objectives inherent in the crew scheduling system. While trying to minimize the system wide crew-related costs, the system is also able to address concern with respect to the number of split duties.     

The Economic Lot Scheduling Problem without Capacity Constraints

This study presents a comprehensive analysis on the Economic Lot Scheduling Problem (ELSP) without capacity constraints. We explore the optimality structure of the ELSP without capacity constraints and discover that the curve for the optimal objective values is piecewise convex with repsect to B, i.e., the values of basic period. The theoretical properties of the junction points on the piecewise convex curve not only provides us the information on “which product i” to modify, but also on “where on the B-axis” to change the set of optimal multpliers in the search process. By making use of the junction points, we propose an effective search algorithm to secure a global optimal solution for the ELSP without capacity constraints. Also, we use random experiments to verify that the proposed algorithm is efficient. The results in this paper lay important foundation for deriving an efficient heuristic to solve the conventional ELSP with capacity constraints.     

考虑机器能耗的绿色作业车间调度问题

针对传统作业车间调度,在保证交货期的前提下,以机器能耗最小为目标研究带有关机/重启策略的绿色车间调度问题。首先建立数学规划模型,然后在遗传算法的框架下,根据问题特点提出了一种局部调整的解码方式,在排产时进行工序的移动并确定其开始加工时刻。最后进行小规模算例运算,验证数学规划模型的有效性,再利用算例对基于局部调整解码和顺序解码的遗传算法进行对比测试,结果表明提出的局部调整解码可以在降低机器能耗的同时提高求解效率。     

双目标突发事件应急救援前摄性调度优化

本文以救援时间最短化与计划鲁棒性最大化为目标,研究突发事件应急救援前摄性调度优化问题。作者首先对所研究问题进行界定,其中计划鲁棒性定义为各活动开始时间可调整时差的总和,任务是在应急预算和救援期限的约束下,确定活动执行模式与开始时间以实现上述两个目标。随后,构建问题的0-1规划优化模型,鉴于其强NP-hard属性,设计禁忌搜索启发式算法。最后用一个算例对研究进行说明,得到如下结论:救援时间随应急预算的增加而缩短,随救援期限的放宽而延长;计划鲁棒性随应急预算的增加或救援期限的放宽而提高;当权重分配系数增大时,应急救援时间先保持不变而后缩短,计划鲁棒性则呈减小趋势。本文研究可为突发事件应急救援的组织与协调提供决策支持。     

A Tabu Search Approach for the Resource Constrained Project Scheduling Problem

An appropriate tabu search implementation is designed to solve the resource constrained project scheduling problem. This approach uses well defined move strategies and a structured neighbourhood, defines appropriate tabu status and tenure and takes account of objective function approximation to speed up the search process. A sound understanding of the problem has helped in many ways in designing and enhancing the tabu search methodology. The method uses diversification, intensification and handles infeasibility via strategic oscillation.The above methodology is tested on existing problems from the literature and also on parametrically generated problems with encouraging results. For comparison of results, optimal solutions are used in the former and lower bounds obtained by Lagrangian heuristics are used in the latter.