通过仿真和自适应遗传算法优化物流园区布局

IF 3.8 Q2 TRANSPORTATION
Cheng Cheng , Gengchen Zhu , Yuting Yan , Zengshuang Li
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引用次数: 0

摘要

提出了一种利用自适应遗传算法(GA)进行物流园区布局设计的创新方法。物流园区布局优化是一个复杂的问题,对货物运输效率和园区整体功能有着重要的影响。在本研究中,我们通过考虑物流园区及其功能区的独特特征来解决选择最合适的路网布局的挑战。自适应遗传算法结合了一种复杂的初始种群生成策略和一种自适应交叉和突变操作,从而导致改进的解决方案。通过严格的模拟和评估,我们比较了不同的路网布局,突出了网格和圆形布局的优势。研究结果为物流园区的规划者和决策者提供了有价值的见解,有助于建立可持续和高效的运输网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing logistics park layouts through simulation and adaptive genetic algorithms
This paper presents an innovative approach to the design of logistics park layouts using an Adaptive Genetic Algorithm (GA). Logistics park layout optimization is a complex problem with significant implications for freight transportation efficiency and overall park functionality. In this study, we address the challenge of selecting the most suitable road network layout by considering the unique characteristics of the logistics park and its functional areas. The Adaptive GA incorporates a sophisticated strategy for initial population generation and an adaptive crossover and mutation operation, leading to improved solutions. Through rigorous simulations and evaluations, we compare different road network layouts, highlighting the advantages of both grid and circular layouts. The findings provide valuable insights for logistics park planners and decision-makers, contributing to sustainable and efficient transportation networks.
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来源期刊
Transportation Research Interdisciplinary Perspectives
Transportation Research Interdisciplinary Perspectives Engineering-Automotive Engineering
CiteScore
12.90
自引率
0.00%
发文量
185
审稿时长
22 weeks
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