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Design and development of a hybrid artificial BEE colony algorithm for the environmental vehicle routing problem

机译:求解环境车辆路径问题的混合人工BEE蚁群算法的设计与开发

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摘要

The vehicle routing problem (VRP) is a critical and vital problem in logistics for the design of an effective and efficient transportation network, within which the capacitated vehicle routing problem (CVRP) has been widely studied for several decades due to the practical relevance of logistics operation. However, CVRP with the objectives of minimizing the overall traveling distance or the traveling time cannot meet the latest requirements of green logistics, which concern more about the influence on the environment. This paper studies CVRP from an environmental perspective and introduces a new model called environmental vehicle routing problem (EVRP) with the aim of reducing the adverse effect on the environment caused by the routing of vehicles. In this research, the environmental influence is measured through the amount of the emission carbon dioxide, which is a widely acknowledged criteria and accounts for the major influence on environment. A hybrid artificial bee colony algorithm (ABC) is designed to solve the EVRP model, and the performance of the hybrid algorithm is evaluated through comparing with well-known CVRP instances. The computational results from numerical experiments suggest that the hybrid ABC algorithm outperforms the original ABC algorithm by 5% on average. The transformation from CVRP to EVRP can be recognized through the differentiation of their corresponding optimal solutions, which provides practical insights for operation management in green logistics.
机译:车辆路径问题(VRP)是物流中设计有效而高效的运输网络的关键和至关重要的问题,由于物流的实际意义,在数十年中,对能力有限的车辆路径问题(CVRP)进行了广泛研究操作。然而,以最小化总行驶距离或总行驶时间为目标的CVRP不能满足绿色物流的最新要求,而绿色物流则更关注对环境的影响。本文从环境角度研究了CVRP,并引入了一种称为环境车辆路径问题(EVRP)的新模型,旨在减少车辆路径对环境的不利影响。在这项研究中,环境影响是通过排放的二氧化碳量来衡量的,二氧化碳的排放量是公认的标准,并且说明了对环境的主要影响。设计了一种混合人工蜂群算法(ABC)来求解EVRP模型,并通过与著名的CVRP实例进行比较来评估混合算法的性能。数值实验的计算结果表明,混合ABC算法的性能平均比原始ABC算法高5%。从CVRP到EVRP的转变可以通过区分其相应的最佳解决方案而得到认可,这为绿色物流的运营管理提供了实用的见识。

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