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Mixed fleet based green clustered logistics problem under carbon emission cap
Sustainable Cities and Society ( IF 11.7 ) Pub Date : 2021-06-05 , DOI: 10.1016/j.scs.2021.103074
Md. Anisul Islam , Yuvraj Gajpal , Tarek Y. ElMekkawy

Sustainable transportation is an ever-demanding matter for cities and societies in light of minimizing global CO2 emissions. This paper introduces the mixed fleet based green clustered logistics problem (MFGCLP) under CO2 emission cap to deal with the sustainable development effort of the transportation industry. The mixed fleet consists of hydrogen vehicles and conventional vehicles. In the proposed distribution problem, customers are clustered in different segments based on similar characteristics. The customers belonging to a cluster must be served by the same vehicle before it visits customers from a different cluster or before it returns to the depot. The CO2 emission of the vehicles is realistically considered as a function of traveled distance, speed, and on-board cargo load. The problem also includes time windows for customers and maximum tour length for the routes. A new hybrid metaheuristic, combining particle swarm optimization (PSO) and neighborhood search, is proposed to solve the problem. Extensive computational experiments have been performed on newly generated problem instances, and benchmark problem instances adopted from the literature. The proposed hybrid PSO proved to be superior to the state-of-the-art algorithms available in the literature.



中文翻译:

碳排放上限下基于混合车队的绿色集群物流问题

考虑到最大限度地减少全球 CO 2排放,可持续交通对于城市和社会来说是一个不断要求的问题。本文介绍了CO 2排放上限下基于混合车队的绿色集群物流问题(MFGCLP),以应对运输业的可持续发展努力。混合车队由氢动力汽车和传统汽车组成。在所提出的分布问题中,客户基于相似的特征聚集在不同的细分市场中。属于一个集群的客户在访问来自不同集群的客户或返回仓库之前,必须由同一辆车服务。二氧化碳2车辆的排放实际上被认为是行驶距离、速度和车载货物负载的函数。该问题还包括客户的时间窗口和路线的最大游览长度。提出了一种结合粒子群优化 (PSO) 和邻域搜索的新混合元启发式算法来解决该问题。已经对新生成的问题实例和从文献中采用的基准问题实例进行了广泛的计算实验。所提出的混合 PSO 被证明优于文献中可用的最先进算法。

更新日期:2021-06-08
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