绿色车辆路径问题的混合增益-蚁群算法

2022 9th International Conference on Soft Computing & Machine Intelligence (ISCMI) Pub Date : 2022-11-26 DOI:10.1109/ISCMI56532.2022.10068439

V. Sangeetha, R. Krishankumar, K. S. Ravichandran, A. Gandomi

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引用次数: 1

摘要

不断增加的碳排放和足迹是造成环境可持续性失衡的主要原因之一，而这主要是由交通造成的。运输是物流配送和供应链的核心功能。针对绿色车辆路径问题，提出了一种增益-蚁群优化和果蝇优化的混合算法，以有效地规划出最短路径并降低总油耗。提出的算法使用埃尔多安和米勒胡克斯数据集进行模拟，并与最知名的解决方案和现有方法进行比较。

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A Hybrid Gain-Ant Colony Algorithm for Green Vehicle Routing Problem

Increasing carbon emissions, and thus footprint, is one of the main reasons for the imbalance in environmental sustainability, which is primarily contributed to transportation. Transportation is a core functionality of logistics distribution and supply chain. In this paper, a hybrid gain-ant colony optimization and fruit fly optimization algorithm for green vehicle routing problem is proposed to plan shortest paths with reduced total fuel consumption efficiently. The proposed algorithm was simulated using the Erdogan and Miller Hooks dataset and compared with best-known solutions and existing methods.

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2022 9th International Conference on Soft Computing & Machine Intelligence (ISCMI)

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