Multi-objective municipal solid waste management recycling problem in fuzzy-rough environment. (2018)

• Record Type: Journal Article
• Authors: Pramanik, Sutapa; Maity, Kalipada; Jana, Dipak Kumar; Mukherjee, Anupam
• Is Part Of: International journal of process management and benchmarking. Volume 8:Number 4(2018)
• Page Start: 443
• Page End: 469
• Publication Date: 2018
• Subjects: municipal solid waste management -- greenhouse gas emission control -- recycling -- fuzzy rough -- fuzzy satisfying method; Industrial engineering -- Periodicals; Total quality management -- Periodicals; Knowledge management -- Periodicals; 658.5005
• Languages: English
• ISSNs: 1460-6739

Abstract

In municipal solid waste (MSW) management, not only economic objectives but also environmental objectives are considered simultaneously. In this paper, a fuzzy rough (Fu-Ro) multi-objective municipal solid waste management problem (MMSWMP) is developed for supporting MSW management, associated greenhouse gas (GHG) emission control and recycling. Here, for the first time, three conflicting objectives are integrally considered, including minimisation of total system cost, minimisation of total GHG emissions from waste management facilities and maximisation of total revenue. The present MMSWMP improves upon the existing single or double objectives waste management optimisation models. Here imprecise cost parameters of the models are expressed as Fu-Ro variables. Some constraints of the system are expressed as chance constraints and Fu-Ro constraints. Multi-objective problem is transformed to single objective one through incorporation of fuzzy satisfying technique. Then it is solved as a general mixed-integer single-objective linear programming problem using a gradient-based optimisation technique - generalised reduced gradient method (Lingo-14.0). Representing different preferences of the decision makers for economic development and environmental-impact, four different planning models are formulated, solved, analysed and compared. The models are numerically illustrated and some sensitivity analysis are presented.