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Urban hazmat transportation with multi-factor
Soft Computing ( IF 3.1 ) Pub Date : 2019-04-01 , DOI: 10.1007/s00500-019-03956-x
Jiaoman Du , Xiang Li , Lei Li , Changjing Shang

Abstract

In this paper, an urban hazmat transportation problem considering multiple factors that tangle with real-world applications (i.e., weather conditions, traffic conditions, population density, time window, link closure and half link closure) is investigated. Based on multiple depot capacitated vehicle routing problem, we provide a multi-level programming formulation for urban hazmat transportation. To obtain the Pareto optimal solution, an improved biogeography-based optimization (improved BBO) algorithm is designed, comparing with the original BBO and genetic algorithm, with both simulated numerical examples and a real-world case study, demonstrating the effectiveness of the proposed approach.



中文翻译:

多因素城市危险品运输

摘要

在本文中,研究了考虑到与实际应用纠缠不清的多个因素的城市危险品运输问题(即天气状况,交通状况,人口密度,时间窗,链接关闭和半链接关闭)。基于多仓库容量限制的车辆路径问题,我们为城市危险品运输提供了多层次的编程公式。为了获得帕累托最优解,设计了一种改进的基于生物地理的优化(改进的BBO)算法,并与原始的BBO和遗传算法进行了比较,并通过仿真数值示例和实际案例研究,证明了该方法的有效性。

更新日期:2020-04-06
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