An interval-parameter stochastic robust optimization model for supporting municipal solid waste management under uncertainty |
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| Authors: | Y Xu GH Huang XS Qin MF Cao Y Sun |
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| Institution: | 1. Sino-Canada Center of Energy and Environmental Research, North China Electric Power University, Beijing 102206, China;2. Centre for Studies in Energy and Environment (CSEE), University of Regina, Regina, Saskatchewan, Canada S4S 0A2;3. School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore;1. Department of Engineering and Inter-University Centre of Theoretical and Experimental Dynamics, University of Messina, Villaggio S. Agata, 98166 Messina, Italy;2. Department of Architecture and Territory and Inter-University Centre of Theoretical and Experimental Dynamics, University “Mediterranea” of Reggio Calabria, Salita Melissari, Feo di Vito, 89124 Reggio Calabria, Italy;1. School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China;2. State Key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University, Changsha 410082, China;3. School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, NSW 2006, Australia;1. National Technical University of Athens, Greece;2. EPEM SA, Greece;3. FACETS SA, Greece;4. Athena Research and Innovation Center, Greece;5. National Observatory of Athens, Greece;1. Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran;2. LCFC, CER Metz – Arts et Métiers Paris Tech, Metz, France;3. Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran;1. School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran;2. Department of Industrial Engineering, College of Engineering, Tarbiat Modares University, Tehran, Iran |
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| Abstract: | A stochastic robust interval linear programming model (IPRO) was developed for supporting municipal solid waste management under uncertainty. The model improves upon the existing stochastic robust optimization (SRO) and interval linear programming (ILP) methods by allowing evaluations of trade-offs among expected costs, cost variability, and risk of violating relax constraints simultaneously, as well as reflections of complex uncertainties through both interval and stochastic theories. A long-term waste management problem was used to demonstrate the applicability of IPRO model. The results indicated that IPRO normally led to interval solutions, where waste-management alternatives could be generated by adjusting the decision-variable values within their intervals. The model could also help waste managers to identify desired policies that under various environmental, economic, system-feasibility and system-reliability constraints. |
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