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Open AccessArticle

FCVLP: A Fuzzy Random Conditional Value-at-Risk-Based Linear Programming Model for Municipal Solid Waste Management

1
School of Fundamental Science, Beijing Polytechnic, Beijing 100176, China
2
Shandong Key Laboratory of Water Pollution Control and Resource Reuse, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China; Shandong Wuzhou Detection Co., Ltd., Jining 273200, China
3
Department of Civil and Environmental Engineering, Brunel University, London UB8 3PH, UK
*
Author to whom correspondence should be addressed.
Climate 2019, 7(6), 80; https://doi.org/10.3390/cli7060080
Received: 16 April 2019 / Revised: 26 May 2019 / Accepted: 31 May 2019 / Published: 6 June 2019
(This article belongs to the Special Issue Environment Pollution and Climate Change)
A fuzzy random conditional value-at-risk-based linear programming (FCVLP) model was proposed in this study for dealing with municipal solid waste (MSW) management problems under uncertainty. FCVLP improves upon the existing fuzzy linear programming and fuzzy random conditional value-at-risk methods by allowing analysis of the risks of violating constraints that contain fuzzy parameters. A long-term MSW management problem was used to illustrate the applicability of FCVLP. The optimal feasibility solutions under various significance risk levels could be generated in order to analysis the trade-offs among the system cost, the feasibility degree of capacity constraints, and the risk level of waste-disposal-demand constraints. The results demonstrated that (1) a lower system cost may lead to a lower feasibility of waste-facility-capacity constraint and a higher risk of waste-disposal-demand constraint; (2) effects on system cost from vague information in incinerator capacity inputs would be greater than those in landfill capacity inputs; (3) the total allowable waste allocation would vary significantly because of the variations of risk levels and feasibility degrees. The proposed FCVLP method could be used to identify optimal waste allocation scenarios associated with a variety of complexities in MSW management systems. View Full-Text
Keywords: fuzzy random conditional value-at-risk; fuzzy linear programming; risk control; decision making; uncertainty; municipal solid waste management fuzzy random conditional value-at-risk; fuzzy linear programming; risk control; decision making; uncertainty; municipal solid waste management
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Wang, D.; Kong, X.; Zhao, S.; Fan, Y. FCVLP: A Fuzzy Random Conditional Value-at-Risk-Based Linear Programming Model for Municipal Solid Waste Management. Climate 2019, 7, 80.

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