MDEALS解决泰国呵叻府陆港木薯淀粉物流网络问题

IF 3.6 Q2 MANAGEMENT Logistics-Basel Pub Date : 2022-10-10 DOI:10.3390/logistics6040072
Chakat Chueadee, P. Kriengkorakot, Nuchsara Kriengkorakot
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引用次数: 0

摘要

背景:本研究旨在建立一个与发电相关的网络,用于将木薯淀粉产品运输到作为泰国呵叻府物流枢纽的陆路港口。方法:将自适应大邻域搜索(ALNS)算法与差分进化(DE)方法相结合进行问题分析,该方法被命名为改进的差分进化自适应大邻域检索(MDEALNS),它是一种新的方法,包括六个步骤,即(1)初始化、(2)突变、(3)重组、(4)用ALNS更新,(5)选择和(6)重复(2)至(5)步骤,直到满足终止条件。MDEALS算法设计了一个物流网络,将最优路线和合适的开/关工厂分配与木薯淀粉的最低运输成本联系起来。以木薯淀粉生产的供应链运作为例进行研究。利用三组测试实例的数据集对所提出的方法进行了测试,并对404个农场、33个工厂和1个陆港进行了案例研究。结果:计算结果表明,MDEALNS方法可以减少距离和燃料成本,并且优于LINGO、DE和ALNS使用的原始方法的最高性能。结论:计算结果表明,MDEALNS方法可以减少距离和燃料成本,并且优于LINGO、DE和ALNS使用的原始方法的最高性能。
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MDEALNS for Solving the Tapioca Starch Logistics Network Problem for the Land Port of Nakhon Ratchasima Province, Thailand
Background: This research aimed to establish a network linked to generation, for the transport route of tapioca starch products to a land port, serving as the logistics hub of Thailand’s Nakhon Ratchasima province. Methods: The adaptive large neighborhood search (ALNS) algorithm, combined with the differential evolution (DE) approach, was used for the problem analysis, and this method was named modified differential evolution adaptive large neighborhood search (MDEALNS) is a new method that includes six steps, which are (1) initialization, (2) mutation, (3) recombination, (4) updating with ALNS, (5) Selection and (6) repeat the (2) to (5) steps until the termination condition is met. The MDEALNS algorithm designed a logistics network linking the optimal route and a suitable open/close factory allocation with the lowest transport cost for tapioca starch. The operating supply chain of tapioca starch manufacturing in the case study. The proposed methods have been tested with datasets of the three groups of test instances and the case study consisted of 404 farms, 33 factories, and 1 land port. Results: The computational results show that MDEALNS method can reduced the distance and the fuel cost and outperformed the highest performance of the original method used by LINGO, DE, and ALNS. Conclusions: The computational results show that MDEALNS method can reduced the distance and the fuel cost and outperformed the highest performance of the original method used by LINGO, DE, and ALNS.
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Logistics-Basel
Logistics-Basel Multiple-
CiteScore
6.60
自引率
0.00%
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0
审稿时长
11 weeks
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