Designing a sustainable logistics network for hazardous medical waste collection a case study in COVID-19 pandemic


Erdem M.

JOURNAL OF CLEANER PRODUCTION, cilt.376, 2022 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 376
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1016/j.jclepro.2022.134192
  • Dergi Adı: JOURNAL OF CLEANER PRODUCTION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Communication Abstracts, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Sustainable logistics, Optimization model, Electric vehicles, Hazardous medical waste, Transportation risk, Adaptive large neighbourhood search, VEHICLE-ROUTING PROBLEM, MATHEMATICAL-MODEL, TIME WINDOWS, OPTIMIZATION
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

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.