Title: The research on two phase pickup vehicle routing based on the K-means++ and genetic algorithms

Authors: Huan Zhao; Yiping Yang

Addresses: School of Management and Engineering, Capital University of Economics and Business, China ' School of Management and Engineering, Capital University of Economics and Business, China

Abstract: A popular topic of interest is the development of an efficient vehicle routing plan, which needs to meet customer requirements and ensure delivery with the lowest cost. This paper established a model of the vehicle routing problem with a time window and static network considering the vehicle type, type of goods, and customer satisfaction requirements to build an optimisation model. By optimising the combination of the K-means++ and genetic algorithms, the problem is transformed into a two stage solution, supplier clustering is performed using the K-means++ algorithm, and the vehicle path is determined using the genetic algorithm in each cluster arrangement. Finally, the optimisation results are compared with the actual delivery data, which demonstrates that the optimisation results are superior to the current vehicle arrangement in terms of vehicle utilisation and cost. Finally, an example is presented to illustrate the feasibility of the proposed algorithm.

Keywords: traffic engineering; VRP optimisation model; two stage; K-means++; genetic algorithm.

DOI: 10.1504/IJWET.2020.107685

International Journal of Web Engineering and Technology, 2020 Vol.15 No.1, pp.32 - 58

Published online: 03 Jun 2020 *

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