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| 1 | 求解N-车探险问题的Memetic烟花算法显示文摘N-车探险问题是一类在燃油约束下安排N辆车的行驶顺序以使车辆行驶最远的NP-hard问题.针对该问题,提出一种融合局部搜索的Memetic烟花算法(MFWA).根据该问题等价于置换排序的特性,设计基于rankedorder value(ROV)规则的编码方式,引入动态爆炸半径,使用烟花算法进行全局搜索;设计插入、交换和反转等邻域操作,增强算法的局部搜索能力;利用实验设计探讨了关键参数对算法性能的影响.基于14个标准问题的测试结果表明:所设计的局部搜索操作有助于增强烟花算法在N-车探险问题上的寻优精度;MFWA的寻优精度、稳定性等整体优于(至少不劣于)标准烟花算法(FWA)、已有的启发式算法(H1-H4)、粒子群优化(PSO)和水波优化(WWO);与MFWA相比,禁忌变邻域局部搜索(TBVLS)用至少55倍的计算时间得到了最大竞争比为1.126的寻优精度.这些结果表明,MFWA能在较短时间内获得较满意的寻优精度. | 刘翱 刘凡熙 冯骁毅 邓旭东 刘波 任亮 | 2018 | 控制与决策2018，33，10： | 5 |
| 2 | Modeling and Solving a Multi-Period Inventory Fulfilling and Routing Problem for Hazardous Materials显示文摘Any potential damage may be severe once an accident occurs involving hazardous materials.It is therefore important to consider the risk factor concerning hazardous material supply chains,in order to make the best inventory routing decisions.This paper addresses the problem of hazardous material multi-period inventory routing with the assumption of a limited production capacity of a given manufacturer.The goal is to achieve the manufacturer's production plan,the retailer's supply schedule and the transportation routes within a fixed period.As the distribution of hazardous materials over a certain period is essentially a multiple travelling salesmen problem,the authors formulate a loadingdependent risk model for multiple-vehicle transportation and present an integer programming model to maximize the supply chain profit.An improved genetic algorithm considering two dimensions of chromosomes that cover the aforementioned period and supply quantity is devised to handle the integer programming model.Numerical experiments carried out demonstrate that using the proposed multiperiod joint decision-making can significantly increase the overall profit of the supply chain as compared to the use of single period decision repeatedly,while effectively reducing its risk. | HU Hao LI Jian LI Xiang SHANG Changjing | 2020 | Journal of Systems Science & Complexity2020，33，3： | 0 |
| 3 | 求解N-车探险问题的离散水波优化算法显示文摘N-车探险问题是一类NP-hard离散优化问题,针对该问题,提出一种融合局部搜索的离散水波优化算法。结合该问题等价于置换排序的特性,设计基于置换序列的编码方式;利用反转、移动、交换等操作重新定义传播、折射和碎浪算子;开发基于插入邻域的局部搜索策略,以增强水波优化算法的局部搜索能力。最后,利用实验设计探讨关键参数对算法性能的影响。基于14个标准问题的测试结果表明:所提方法的寻优精度、稳定性等整体优于标准水波优化算法、粒子群算法、烟花算法和启发式算法H1~H4;与离散水波优化算法相比,基于禁忌搜索的变邻域搜索算法用至少66.6倍的计算时间得到了最大相对偏差比为0.017的寻优精度。结果表明,离散水波优化算法能在较短时间内获得较满意的解。 | 刘翱 邓旭东 任亮 杨怡欣 | 2020 | 系统管理学报2020，29，3： | 0 |
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