求解带软时间窗多车场多车型车辆路径问题的一种改进蚁群算法(英文)

被引：39

作者：

汤雅连 ^{[1
]}

蔡延光 ^{[1
]}

杨期江 ^{[2
]}

机构：

[1] 广东工业大学自动化学院

[2] 华南理工大学机械与汽车工程学院

来源：

Journal of Southeast University(English Edition) | 2015年 / 31卷 / 01期

关键词：

车辆路径问题; 软时间窗; 改进蚁群优化算法; 客户服务优先级; 遗传算法;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

140502 [人工智能];

摘要：

考虑实际生活中带多种扩展特征(如多车场、多车型、客户服务优先级、时间窗等)的车辆路径问题应用广泛,建立带软时间窗多车场多车型车辆路径问题的数学模型,并提出一种改进的蚁群优化算法(IACO)求解该模型.首先,根据就近原则将客户分组,并通过扫描算法构造初始路径;其次,通过引入遗传算子并自适应地调整交叉概率和变异概率来提高算法的全局收敛能力,且采用平滑机制来提高蚁群优化算法的性能;最后,采用3-opt策略来提高算法的局部搜索能力.将提出的算法应用在3个随机产生的实例中,仿真表明提出的IACO在收敛速度和解质量两方面都优于现有的3种算法,证明提出的算法是有效可行的,且提出的模型具有一定的实际意义.

引用

页码：94 / 99

页数：6

共 9 条

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