在分销仓库中用于卡车管理的新型变量邻里搜索启发式问题
Akram Y Sarhan1, Loai Kayed B Melhim2, Mahdi Jemmali3,4,5,6
1Department of Information Technology, College of Computing and Information Technology at Khulis, University of Jeddah, Jeddah, Saudi Arabia.
PeerJ. Computer science
|October 23, 2023
概括
本研究介绍了一种智能元启发式解决方案,以优化供应链中的卡车卸货操作. 拟议的系统通过减少卸载时间和运营成本来提高效率.
科学领域:
- 运营研究 运营研究
- 供应链管理 供应链管理
- 物流物流物流物流物流是什么
背景情况:
- 物流和采购管理是关键的经济挑战,运输和仓库运营是主要的成本驱动因素.
- 有效的仓库管理对于及时交付产品和降低运营成本至关重要.
- 卡车卸载带来了重大挑战,特别是未知或可变的卡车数量和卸载时间.
研究的目的:
- 在有限的仓库场景中解决卡车卸货运营问题.
- 通过最大限度地减少卡车卸载时间来提高供应链效率.
- 开发一个智能元启发式仓库管理解决方案.
主要方法:
- 开发一个智能元启发式仓库管理解决方案.
- 使用调度规则,随机化,变换和代方法.
- 为卡车卸货问题提出和评估四种不同的启发式.
主要成果:
- 拟议的解决方案大大减少了整体卡车卸载时间.
- 性能最好的算法在测试案例中实现了78.7%的使用率.
- 最优的算法证明了最小的平均差距为0.001和平均运行时间为0.0053秒.
结论:
- 智能元启发方法有效地优化了卡车卸货操作.
- 开发的启发式提供了一个强大的解决方案,用于管理复杂的物流挑战.
- 这些发现有助于提高供应链管理的效率和降低成本.
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