蚁群优化算法
车辆路径问题
数学优化
计算机科学
布线(电子设计自动化)
收入
蚁群
运筹学
算法
工程类
数学
业务
计算机网络
会计
作者
Yongbo Li,Hamed Soleimani,Mostafa Zohal
标识
DOI:10.1016/j.jclepro.2019.03.185
摘要
Vehicle routing problem (VRP) is one of the widely researched areas in transportation science, mainly due to the potential cost savings and service improvement opportunities which brings to organizations involved in physical distribution of goods. In this paper, we develop a multi-depot green vehicle routing problem (MDGVRP) by maximizing revenue and minimizing costs, time and emission, and then, apply an improved ant colony optimization (IACO) algorithm that aims to efficiently solve the problem. The IACO model developed in this research uses an innovative approach in updating the pheromone that results in better solutions. The results achieved through the IACO demonstrate satisfying performance, which have higher solution quality when compared to the conventional ACO. The IACO algorithm used in this paper demonstrated a good level of responsiveness and simplicity when solving MDGVRP with multiple objectives.
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