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An inexact inventory-theory-based chance-constrained programming model for solid waste management |
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| Authors: | XiuJuan Chen GuoHe Huang MeiQin Suo Hua Zhu Cong Dong |
| Institution: | 1. Environmental Systems Engineering Program, Faculty of Engineering and Applied Science, University of Regina, Regina, SK, S4S 0A2, Canada 2. School of Urban Construction, Hebei University of Engineering, Handan, 056038, Hebei, China 4. S-C Energy and Environmental Research Academy, North China Electric Power University, Beijing, 102206, China 5. Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK, S4S 0A2, Canada 3. MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing, 102206, China |
| Abstract: | In this study, an inexact inventory-theory-based chance-constrained programming (IICP) model is proposed for planning waste management systems. The IICP model is derived through introducing inventory theory model into a general inexact chance-constrained programming framework. It can not only tackle uncertainties presented as both probability distributions and discrete intervals, but also reflect the influence of inventory problem in decision-making problems. The developed method is applied to a case study of long-term municipal solid waste (MSW) management planning. Solutions of total waste allocation, waste allocation batch and waste transferring period associated different risk levels of constraint violation are obtained. The results can be used to identify inventory-based MSW management planning with minimum system cost under various constraint-violation risks. Compared with the ICP model, the developed IICP model can more actually reflect the complexity of MSW management systems and provide more useful information for decision makers. |
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