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Title: Tabu search and constraint programming-based approach for a real scheduling and routing problem

Authors: Abdellah El Fallahi; El Yaakoubi Anass; Mohammad Cherkaoui

Addresses: Modeling and Optimization of Industrials and Logistics Systems, National School of Applied Science, University AbdelMaleek Essaadi of Tetouan, Morocco ' Modeling and Optimization of Industrials and Logistics Systems, National School of Applied Science, University AbdelMaleek Essaadi of Tetouan, Morocco ' Modeling and Optimization of Industrials and Logistics Systems, National School of Applied Science, University AbdelMaleek Essaadi of Tetouan, Morocco

Abstract: Constraint programming method (CPM) has gained much attention in the last years since it proved a great efficiency to model and solve many combinatorial problems like scheduling, assignment and routing problems. In this paper, we first present a CPM model for a real scheduling and routing problem (SRP) faced by a company of water and electricity distribution. The problem aims to minimise the total distance travelled by the company's technicians to the clients' locations in order to carry out some services. To solve the studied SRP three CPM-based solution methods are proposed: an exact method (branch and prune), a local search meta-heuristic and a hybrid algorithm which combine tabu search and constraint programming method. The proposed solution methods have been tested using three sets of instances. The two first sets are generated randomly, they represent small and large scale instances, while the third one contain the real instances provided by the company with which we are working. The results obtained by the three methods show clearly the superiority of the hybrid algorithm over the two others methods.

Keywords: constraint programming methods; CPM; tabu search; scheduling and routing problem; SRP.

DOI: 10.1504/IJAMS.2020.105298

International Journal of Applied Management Science, 2020 Vol.12 No.1, pp.50 - 67

Received: 08 Oct 2018
Accepted: 20 Nov 2018

Published online: 11 Feb 2020 *

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