An integrated multi-objective model for disaster waste clean-up systems optimization. (September 2022)

• Record Type: Journal Article
• Authors: Cheng, Cheng; Lu, Jia-Wei; Zhu, Rui; Xiao, Zuopeng; Costa, Alysson M.; Thompson, Russell G.
• Is Part Of: Transportation research. Volume 165(2022)
• Publication Date: 2022-09
• Subjects: Disaster waste management -- Heavy-duty vehicles -- Environmental emission -- Mixed integer programming -- Optimization -- Pareto frontier; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2022.102867
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: A multi-objective model to optimise a two-echelon disaster waste clean-up system. Optimise the activities of heavy-duty vehicles involved in disaster waste clean-up. Minimise the environmental impacts, economic costs, and total waste clean-up time. Generate a Pareto frontier with three objectives to support decision-making. Abstract: Post-disaster waste clean-up systems are complex and expensive operations that need to consider multiple stakeholders with different objectives. We propose a mixed-integer programming model that models the waste clean-up operations as a two-echelon system. The model decides on the location of waste processing facilities, the use of demolition resources, and the number and type of vehicles to be assigned to each echelon at each time slot of the planning horizon. The objectives considered in the model include minimizing environmental impacts, economic costs, and total time spent on the operations. Numerical results obtained on a case study based on the '2009 Victoria Black Saturday Bush-fires' case and on synthetically generated instances are used to obtain Pareto frontiers. The research concludes that the three objectives considered are indeed conflictive, and the explicit consideration of each goal can help decision-makers find the best trade-off solutions.