Multi-depot vehicle routing problem based on customer satisfaction

被引:2
|
作者
Rajak, Sonu [1 ]
Parthiban, P. [1 ]
Dhanalakshmi, R. [2 ]
机构
[1] Natl Inst Technol, Dept Prod Engn, Tiruchirappalli 620015, India
[2] Natl Inst Technol, Dept Comp Sci & Engn, Nagaland 797103, Dimapur, India
关键词
vehicle routing problem; VRP; combinatorial optimisation; K-means clustering algorithm; ant colony optimisation; ACO; customers satisfaction; fuzzy time windows; SOFT TIME WINDOWS; OPTIMIZATION; ALGORITHM; MODEL;
D O I
10.1504/IJSTM.2020.106693
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Nowadays, meeting the customer's demands in the shortest time and least cost is the most challenging task of maintaining any supply chain. Vehicle routing problem (VRP) plays an important role in the logistics. In typical VRP, customers' are used to serving as a single depot, but in real-life single depot will not be sufficient to meet the customer's demand or customers' satisfaction. In this context, this article presents the multi-depot vehicle routing problem based on customer's satisfaction (MDVRPCS). Since MDVRPCS is an NP-hard problem so, ant colony optimisation (ACO) has been proposed to solve the MDVRPCS. The proposed algorithms have two phases. The first phase involves clustering the nodes into a desired number of groups. This has been done by using K-means clustering algorithm. The second phase involves optimisation of routes for each cluster. This is achieved by using ACO. The proposed algorithm has been tested for well-know problem instances from the literature. The results show that the algorithm is capable of obtaining good optimal solutions.
引用
收藏
页码:252 / 265
页数:14
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