Designing a sustainable logistics network for hazardous medical waste collection a case study in COVID-19 pandemic. (20th November 2022)

• Record Type: Journal Article
• Authors: Erdem, Mehmet
• Is Part Of: Journal of cleaner production. Volume 376(2022)
• Publication Date: 2022-11-20
• Subjects: Sustainable logistics -- Optimization model -- Electric vehicles -- Hazardous medical waste -- Transportation risk -- Adaptive large neighbourhood search; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2022.134192
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: The process of collecting and transporting hazardous medical waste poses a potential threat to the environment and public safety. Furthermore, the waste management system faces higher transportation costs due to the increasing human activities related to rapid population growth. The absence of an efficient and safe logistics network for the timely collection and transportation of hazardous wastes may have negative effects on the environment and public health. Therefore, more sustainable transportation of hazardous waste services is a necessity This paper attempts to design a sustainable network for hazardous medical waste collection services during the COVID-19 pandemic. An electric medical waste collection vehicle routing problem is introduced to construct optimal routes and rosters for a fleet of electric vehicles as well as cover their choice of charging technologies, times and locations. This problem allows us to minimize the health risk of hazardous medical waste while providing cost-effective, zero-emission waste management logistics. Therefore, this problem covers environmental and economic objectives to achieve sustainable development. An effective heuristic that covers adaptive large neighbourhood search and a local search is designed to deal with the complex problem. A series of extensive computational experiments is carried out using real-life benchmark instances to assess the performance of the algorithm. A sensitivity analysis is also conducted to investigate the effect of multiple charger types on the cost and risk objectives. The experiment results indicate that mixed-use of different charger types can reduce the total energy cost and transport risk compared to the case of using only a single charger. Graphical abstract: Highlights: Proposing a new model for the hazardous waste collection problem. Minimizing total energy cost and transfer risk of hazardous waste in Covid-19. An adaptive large neighbourhood search is developed as a solution procedure. Extensive analysis on real-life data are conducted to provide several insights. Investigating the impact of mixing charger types on the objectives.