Xiaosheng Qin, Ye Xu, and Tianyi Xu
Solid waste management, chance constrained, fuzzy set, genetic algorithm
A fuzzy chance-constrained programming (GAFCCP) model aided with genetic algorithm (GA) for solution was proposed for solid waste management under uncertainty. GAFCCP allowed some constraints with fuzzy variables to be satisfied at specified confidence levels, leading to cost-effective solutions under acceptable risk magnitudes. GA was capable of tackling some complicated forms of fuzzy membership functions and used to seek the optimal solutions by progressively evaluating the performances of individual chromosomes. A long-term waste management problem was used to demonstrate the applicability of the proposed model. The results demonstrated that GAFCCP model could help waste managers tackle complex un- certainties related to solid waste management system and gain an in-depth insight into the trade-off between the system cost and system-failure risk. The model could also help waste managers identify desired policies in light of various environmental and economic constraints.
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