A multi-objective location-allocation optimization for sustainable management of municipal solid waste

Hao Yu () and Wei Deng Solvang ()
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Hao Yu: UiT The Arctic University of Norway
Wei Deng Solvang: UiT The Arctic University of Norway

Environment Systems and Decisions, 2017, vol. 37, issue 3, 289-308

Abstract: Abstract The location problem of treatment and service facilities in municipal solid waste (MSW) management system is of significant importance due to the socioeconomic and environmental concerns. The consideration of waste treatment costs, environmental impact, greenhouse gas (GHG) emissions, social fairness as well as other relevant aspects should be simultaneously taken into account when a MSW management system is planned. Development of sophisticated decision support tools for planning MSW management system in an economic-efficient and environmental friendly manner is therefore important. In this paper, a general multi-objective location-allocation model for optimally managing the interactions among those conflicting factors in MSW management system is proposed. The model is comprised of a three-stage conceptual framework and a mixed integer mathematical programming. The inclusion of environmental impact and GHG emission objectives push the output of the model tightening toward more environmentally friendly and sustainable solutions in MSW management. The application of this model is demonstrated through an illustrative example, and the computational efficiency of the programming is also tested through a set of incremental parameters. Latter in this paper, a comparison with previous case studies of MSW system design is presented in order to show the applicability and adaptability of the generic model in practical decision-making process, and the perspectives of future study are also discussed.

Keywords: Waste management; Environmental impact; Sustainable development; Municipal solid waste; MSW; Multi-objective programming; Mixed integer programming; Location-allocation problem (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10669-017-9632-y

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