一个人工蜂群优化算法,用于解决模糊容量后勤配送中心问题
Yasser M Ayid1, Mohammad Zakaraia2, Mohamed Meselhy Eltoukhy3
1Mathematics Department, Faculty of Sciences and Arts, Al-Kamil University of Jeddah, Saudi Arabia.
MethodsX
|October 9, 2024
概括
本研究介绍了一种模糊模型,用于在不确定的工厂需求下优化配送中心选择. 它介绍了混合的人工蜜蜂群算法和基准问题,以提高物流规划和决策.
科学领域:
- 运营研究 运营研究
- 物流管理物流管理
- 模糊的集合理论 模糊的集合理论
背景情况:
- 有能力的物流配送中心问题涉及选择最佳的配送中心以满足工厂的需求.
- 现有的模型经常与不确定的需求作斗争,需要对现实世界的应用进行强大的方法.
- 模糊逻辑提供了一个框架,用于模拟和管理需求预测和网络设计中的不确定性.
研究的目的:
- 开发一种方法论方法来解决模糊容量物流配送中心问题.
- 根据固定成本,容量和模糊工厂需求,优化分销中心的选择.
- 提供一个基准数据集和先进的算法,用于研究和在物流分销实际应用.
主要方法:
- 模糊需求通过将模糊需求转换为清晰的价值来解决模糊容量后勤配送中心问题的数学公式.
- 三种不同的人工蜂群算法变体的混合化,采用启发式方法.
- 应用Taguchi的直角数组来系统地优化算法参数.
主要成果:
- 为在不确定的需求下选择配送中心而开发了一个模糊模型.
- 创建了20个基准问题,以促进研究和比较分析.
- 混合人工蜂群算法在解决问题的复杂性方面表现出有效性.
结论:
- 提出的方法方法有效地解决了模糊容量后勤配送中心的问题.
- 开发的算法和基准问题有助于推进不确定的物流规划研究.
- 该研究提供了一个全面的工具包,用于优化不确定需求的配送中心选择.
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