A decomposition algorithm for organic solid waste supply chain optimization under uncertainty

Yousef Saif, Muhammed Rizwan, Ali Almansoori, Ali ElKamel

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations


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.

Original languageBritish English
Pages (from-to)3284-3289
Number of pages6
JournalEnergy Procedia
StatePublished - 2019
Event10th International Conference on Applied Energy, ICAE 2018 - Hong Kong, China
Duration: 22 Aug 201825 Aug 2018


  • L-shaped decomposition algorithm
  • Organic MSW management
  • Stochastic optimization
  • Supply chain


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