Hybrid Clustering Algorithms with GRASP to Construct an Initial Solution for the MVPPDP

  • Abeer I Alhujaylan Qassim University
  • Manar I Hosny
Keywords: Multi-vehicle profitable pickup and delivery problem, K-means clustering algorithm, ant colony optimisation, greedy randomised adaptive search procedure, metaheuristic algorithms.

Abstract

Mobile commerce (m-commerce) contributes to increasing the popularity of electronic commerce (e-commerce), allowing anybody to sell or buy goods using a mobile device or tablet anywhere and at any time. As demand for e-commerce increases tremendously, the pressure on delivery companies increases to organise their transportation plans to achieve profits and customer satisfaction. One important planning problem in this domain is the multi-vehicle profitable pickup and delivery problem (MVPPDP), where a selected set of pickup and delivery customers need to be served within certain allowed trip time. In this paper, we proposed hybrid clustering algorithms with the greedy randomised adaptive search procedure (GRASP) to construct an initial solution for the MVPPDP. Our approaches first cluster the search space in order to reduce its dimensionality, then use GRASP to build routes for each cluster. We compared our results with state-of-the-art construction heuristics that have been used to construct initial solutions to this problem. Experimental results show that our proposed algorithms contribute to achieving excellent performance in terms of both quality of solutions and processing time.

Published
2020-05-20
Section
Articles on Computers