Municipal Solid Waste Management Using Multiobjective Optimization with Uncertain Parameters
Publication: Journal of Hazardous, Toxic, and Radioactive Waste
Volume 23, Issue 4
Abstract
Municipal solid waste (MSW) management involves economic and technical aspects and regulatory normative constraints. The selection of an optimal configuration for transportation routes, treatment technologies, and disposal sites is of prime importance in MSW management. In this paper, a mixed integer linear optimization model is presented, taking into account uncertainty in waste quantity and the capacity of waste treatment facilities. The MSW management was planned in order to reduce the total cost involved in solid waste management, the total environmental risk due to treatment facilities, and the volume of waste at the sources. A population-weighted vehicle routing (PWVR) optimization model was used for locating optimized waste sources/centers. The analysis of single objectiveoptimization, multiobjective optimization, and goal programming reveal that total costs very to some extent with the varying of waste quantity and quality of incinerator. Uncertainty analysis for waste quantity (), unrecovered waste (), and capacity of waste treatments/disposal facilities () considered three cases. In Case 1, the optimization model was run for different values of with increments of 0.1 keeping a constant value of . In Case 2, the model was run for different values of with increments 0.1 and a constant value of . Case 3 represented simultaneously changing values of and with increments of 0.1. Uncertainty analysis revealed that waste quantity affect more on the planning of waste management than the capacity of the treatment/disposal facilities. The total cost obtained in Case 2 was more dependent on the facilities than on the quantity of waste. The optimized value for total environmental risk and waste volume reduction was obtained with Cases 2 and 3 only. Total cost obtained using single objective optimization was lower, in general, than the value obtained by multiobjective optimization and goal programming.
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©2019 American Society of Civil Engineers.
History
Received: Sep 21, 2018
Accepted: Apr 8, 2019
Published online: Jul 31, 2019
Published in print: Oct 1, 2019
Discussion open until: Dec 31, 2019
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