Variable neighborhood strategy adaptive search for solving green 2-echelon location routing problem
Variable neighborhood strategy adaptive search for solving green 2-echelon location routing problem
复制标题
求解绿色2梯队位置路由问题的变邻域策略自适应搜索
DOI：
10.1016/j.compag.2020.105406
复制
发表时间：
2020
期刊：
影响因子：
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通讯作者：
Chalermchat Theeraviriya
中科院分区：
文献类型：
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作者：
R. Pitakaso;Kanchana Sethanan;Chalermchat Theeraviriya
本文提出了绿色2梯队位置路由问题（G2ELRP），它是有能力位置路由问题（CLRP）和2梯队位置路由问题（2ELRP）的变体，它处理的是两个层次都需要路由决策的集合问题。G2ELRP的目标是根据两个梯队的距离和路况将总油耗降至最低。在G2ELRP中，可以为客户提供多次服务被认为是一个新的约束。由于其复杂性，G2ELRP需要一个复杂的问题表述。提出了一种新的可变邻域策略自适应搜索（VaNSAS）算法来解决这一问题。计算结果表明，VaNSAS算法有效地解决了案例研究问题，并优于所有其他提出的启发式算法。G2ELRP模型比传统LRP模型节省了3.71%的燃料成本。这表明，该系统不仅可以有效地降低橡胶物流成本，而且可以应用于其他相关的农业工业。
This paper presents the green 2-echelon location routing problem (G2ELRP) which is a variant of the capacitated location-routing problem (CLRP) and the 2-echelon location routing problem (2ELRP), in that it deals with the collection problem for which routing decisions at both levels are required. The G2ELRP aims to minimize the total fuel consumption depending on the distance and the road conditions in both echelons. In the G2ELRP, that a customer can be served more than once is considered as a new constraint. Due to its complexity, the G2ELRP requires a complex problem formulation. A new variable neighborhood strategy adaptive search (VaNSAS) algorithm as a solution approach is introduced to solve the problem. The computational results indicate that the VaNSAS algorithm efficiently solves the case study problem and outperforms all other proposed heuristics. The G2ELRP model saved fuel cost by 3.71% over the traditional LRP. This demonstrates that the proposed VaNSAS is very efficient and not only useful for decreasing costs of rubber logistics, but also for application to other related agro-industries.