A multi-compartment VRP model for the health care waste transportation problem

• Published in: Journal of computational science Vol. 72; p. 102104
• Main Authors: Ouertani, Nasreddine, Ben-Romdhane, Hajer, Nouaouri, Issam, Allaoui, Hamid, Krichen, Saoussen
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2023; Elsevier
• Subjects: Adaptive genetic algorithm; Computer Science; Health-care waste; Multi-compartment vehicle routing problem; Statistical pre-post testing; Statistical pre-post testing; Multi-compartment vehicle routing problem; Adaptive genetic algorithm; Health-care waste
• ISSN: 1877-7503; 1877-7511
• DOI: 10.1016/j.jocs.2023.102104

Health-care waste (HCW) is a special category of refuse generated when providing health care and can comprise materials with infectious and/or toxic characteristics. The disposal of this waste involves its transport from health-care facilities to treatment centers. This step can be threatening to humans and the environment if not managed with the utmost care. To ensure the safe management of HCW, this article proposes a new model for HCW transportation that separates hazardous from non-hazardous waste along the transportation route. The proposed model is based on the multi-compartment vehicle routing problem, where each type of waste is carried in a dedicated compartment, and the objective is to minimize the total route cost. Considering the NP-hardness of the problem, an adaptive genetic algorithm is proposed based on the results of statistical pre-post testing of the population. The experimental study, conducted on benchmark instances and real data instances, show the efficiency of the proposed approach against state-of-the-art algorithms. •The healthcare waste (HCW) transportation problem is modeled as a multicompartment VRP.•An Adaptive GA based on pre-post testing of the population is introduced as a solution approach for the HCW problem.•The effectiveness of the proposed algorithm is evaluated against CPLEX and the best existing results.•A case study is presented to highlight the potential for handling the problem under study.