A time-dependent location-routing problem of hazardous material transportation with edge unavailability and time window. (1st November 2021)

• Record Type: Journal Article
• Authors: Tasouji Hassanpour, Saeed; Ke, Ginger Y.; Tulett, David M.
• Is Part Of: Journal of cleaner production. Volume 322(2021)
• Publication Date: 2021-11-01
• Subjects: Hazardous materials -- Location-routing problem -- Time window -- Time-dependent -- Uncertainty -- Disruption; 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.2021.128951
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: The transportation of hazardous materials (hazmat) is an inseparable component of any industrial society, where truck transportation is the most applied transportation solution for hazmat due to its versatility and flexibility, especially for short-distance and direct shipments. This paper explores the application of robust optimization in hazmat location-routing problems with edge unavailability, time-dependent parameters, and delivery time window. To be specific, random disruptions are formulated as a scenario-based robust optimization model, which is integrated with a vehicle routing problem with time windows, and then solved by an augmented epsilon constraint method. In applying the robust optimization, variabilities in cost and risk functions are introduced as critical indicators for designing robust and reliable transportation plans. In the end, the model is applied to a real-world hazmat transportation network, from which practical insights are derived. The resulting assessments shed light on the trade-off between hazmat risk versus cost, and introduce several useful indicators to facilitate the carrier in making appropriate decisions. Graphical abstract: Highlights: The location-routing decision for hazmat is studied considering multiple paths between nodes. A scenario-based robust optimization method is developed to cope with edge unavailability. Time-dependent parameters and time windows are integrated with the model. Several useful indicators are defined to derive practical managerial insights. A real-world inter-city case study is applied to illustrate the applicability of the model.