设施间散装物料转运系统异构车队规模最优化的封闭式排队网络方法

Logistics Pub Date : 2024-03-04 DOI:10.3390/logistics8010026
Mohamed Amjath, L. Kerbache, James MacGregor Smith
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引用次数: 0

摘要

背景:本研究探讨了在一个具有异构卡车车队的系统中优化车队规模的问题,旨在最大限度地降低设施间物料转运业务的运输成本。研究方法使用封闭式排队网络(CQN)对材料转运过程进行建模,该网络考虑了异构节点以及根据各种卡车类型及其运输材料的独特性而定制的服务时间。优化问题被表述为混合整数非线性编程(MINLP),属于 NP-Hard,使得精确解的计算具有挑战性。为克服这一难题,我们采用了一种数值近似方法,即改进的顺序二次编程(SQP)方法和均值分析(MVA)算法。使用离散事件模拟 (DES) 模型进行了验证。结果:所提出的分析模型在一家钢铁制造厂的材料传输过程中进行了测试。结果表明,与仿真方法相比,分析模型实现了异构卡车车队规模的可比优化,并显著缩短了响应时间。此外,对包括响应时间、利用率和周期时间在内的性能指标进行评估后发现,分析和模拟结果之间的差异极小,分别约为±8%、±8%和±7%。结论:这些研究结果肯定了所介绍的分析方法在优化异构卡车车队的设施间物料转运操作方面的稳健性,展示了其在现实世界中的应用。
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A Closed Queueing Networks Approach for an Optimal Heterogeneous Fleet Size of an Inter-Facility Bulk Material Transfer System
Background: This study addresses optimising fleet size in a system with a heterogeneous truck fleet, aiming to minimise transportation costs in interfacility material transfer operations. Methods: The material transfer process is modelled using a closed queueing network (CQN) that considers heterogeneous nodes and customised service times tailored to the unique characteristics of various truck types and their transported materials. The optimisation problem is formulated as a mixed-integer nonlinear programming (MINLP), falling into the NP-Hard, making exact solution computation challenging. A numerical approximation method, a modified sequential quadratic programming (SQP) method coupled with a mean value analysis (MVA) algorithm, is employed to overcome this challenge. Validation is conducted using a discrete event simulation (DES) model. Results: The proposed analytical model tested within a steel manufacturing plant’s material transfer process. The results showed that the analytical model achieved comparable optimisation of the heterogeneous truck fleet size with significantly reduced response times compared to the simulation method. Furthermore, evaluating performance metrics, encompassing response time, utilisation rate, and cycle time, revealed minimal discrepancies between the analytical and the simulation results, approximately ±8%, ±8%, and ±7%, respectively. Conclusions: These findings affirm the presented analytical approach’s robustness in optimising interfacility material transfer operations with heterogeneous truck fleets, demonstrating real-world applications.
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