A circular economy solid waste supply chain management based approach under uncertainty. (December 2017)

• Record Type: Journal Article
• Authors: Saif, Yousef; Rizwan, Muhammad; Almansoori, Ali; Elkamel, Ali
• Is Part Of: Energy procedia. Volume 142(2017)
• Page Start: 2971
• Page End: 2976
• Publication Date: 2017-12
• Subjects: MSW supply chain -- stochastic optimization -- Bender decomposition algorithm; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.12.316
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: Unconscious storage of municipality solid waste (MSW) in landfills is a traditional practice in the past. Economic, environmental, and social impacts of landfills have motivated interest in the sustainable utilization of the MSW in order to bring values. This can be attained by exploring possible production of valuable products from the MSW constituents. In this study, we cover the MSW supply chain network through different echelons under uncertainty. The first echelon represents collection/transfer stations where the tasks of MSW collection and sorting the MSW into its constituents or sub-waste are performed. The second echelon represents locations where the sub-wastes are distributed to several technologies in order to produce valuable products. In the third echelon, these products are distributed to several markets to satisfy products demand. A stochastic two stage MILP model is formulated to examine the effects of the model parameter uncertainties. Due to the model complexity, a Bender decomposition algorithm is developed to find the model optimal solution. A case study will be presented to show the application of the mathematical programming formulation.