Integrated Modeling for Optimal Municipal Solid Waste Management Strategies under Uncertainty

Abstract

In this study, an inexact fuzzy-probabilistic programming (IFPP) method is advanced for developing optimal municipal solid waste (MSW) management strategy with uncertain information. The IFPP can support the assessment of risk of violating constraints associated with fuzzy and random features. The developed method is applied to a case study of long-term MSW management planning in the city of Changchun, China. Violations for transfer-station capacity constraints are allowed under a range of probability and possibility levels, which are related to trade-offs between the system cost and the constraint-violation risk. The results indicate that useful solutions for planning the MSW management practices have been generated. They are valuable for supporting the identification of efficient waste-flow allocation patterns, the long-term capacity planning of the city’s waste management system, and the formulation of local policies regarding waste management under uncertainty.