A decomposition algorithm for organic solid waste supply chain optimization under uncertainty. (February 2019)

• Record Type: Journal Article
• Authors: Saif, Yousef; Rizwan, Muhammed; Almansoori, Ali; Elkamel, Ali
• Is Part Of: Energy procedia. Volume 158(2019)
• Page Start: 3284
• Page End: 3289
• Publication Date: 2019-02
• Subjects: Organic MSW management -- supply chain -- stochastic optimization -- L-shaped decomposition algorithm; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2019.01.982
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: Storage of municipality solid waste (MSW) in landfills is a common practice of the past. Negative impacts of landfills have motivated interest in the sustainable utilization of MSW. In this study, we cover the treatment of the organic MSW supply chain problem. The supply chain network is composed by several arcs connecting sources of organic MSW by treatment facilities, and markets imposing demand for power. A two-stage stochastic MILP model is formulated to examine the effects of the supply-demand, and power price uncertainties. The first stage decision variables involve technology and capacity selection. The second stage decision variables deal with transportation, and power production. The main contribution of the research study is the application of an L-shaped decomposition algorithm to solve a large scale organic MSW supply chain model under uncertainty. Another contribution is the application of a minmax regret risk model to analyze the financial risk in the organic MSW supply chain problem. A case study is examined to show the application of the mathematical programming formulation.