Title: Effective GA approach for municipal solid waste collection: dynamic capacitated vehicle routing in smart cities

Authors: Abdelfetah Hentout; Abderraouf Maoudj; Ahmed Kouider; Mustapha Aouache

Addresses: Centre de Développement des Technologies Avancées (CDTA), Division Productique et Robotique (DPR), BP 17, Baba Hassen, 16303, Algiers, Algeria ' University of Southern Denmark (SDU), SDU Biorobotics, Maersk Mc-Kinney Moller Institute (MMMI), Campusvej 55, DK-5230, Odense M, Denmark ' Centre de Développement des Technologies Avancées (CDTA), Division Productique et Robotique (DPR), BP 17, Baba Hassen, 16303, Algiers, Algeria ' Centre de Développement des Technologies Avancées (CDTA), Division Télécom (DT), BP 17, Baba Hassen, 16303, Algiers, Algeria

Abstract: Currently, municipal solid waste (MSW) collection is based on ineffective and inflexible static routing models done once a day by trucks. Given a set of fixed bins distributed over a specified area, trucks move along their predefined routes to collect the bins contents. It is also revealed that logistics costs for collection and recycling represent 95% of total cost; thus, minimising total travelled distances using minimum vehicles is of a key importance. This paper presents a genetic algorithm-based solution for municipal solid waste collection and monitoring at smart cities modelled as a capacitated vehicles routing problem (CVRP). This solution adopts two crossover techniques and three mutation methods applied on the population divided into three subsets. Experimental results over various benchmarks show the effectiveness and superiority of the proposed approach in terms of runtime and solution quality. Finally, a real case study of 50 sites (49 bins + a depot) and ten trucks is deployed in the City of Baba Hassen, Algiers, Algeria.

Keywords: municipal solid waste collection; capacitated vehicle routing problem; CVRP; genetic algorithms; smart cities.

DOI: 10.1504/IJAISC.2022.130561

International Journal of Artificial Intelligence and Soft Computing, 2022 Vol.7 No.4, pp.329 - 352

Received: 09 May 2022
Received in revised form: 20 Nov 2022
Accepted: 30 Nov 2022
Published online: 27 Apr 2023 *

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