Municipal Solid Waste–Flow Allocation Planning with Trapezoidal-Shaped Fuzzy Parameters

Abstract

A modified trapezoidal-shaped fuzzy chance-constrained mixed-integer programming (TFCMP) model was advanced for municipal solid waste (MSW) management. Compared with conventional methods, TFCMP was advantageous in handling fuzzy-type uncertainties in both the left- and right-hand sides of model constraints and could be used to reflect the possibility of constraints violation at predefined confidence levels. Mixed-integer programming (MIP) was embedded into the general framework of TFCMP for handling capacity-expansion issues. The solid waste management system in a typical Chinese city was used to demonstrate the applicability of TFCMP. Study results indicated that a variety of cost-effective MSW-flow allocation solutions could be obtained from TFCMP under various scenarios of system reliability. A trade-off between the total system cost and the reliability of satisfying model constraints can be analyzed to gain an in-depth insight into the characteristics of MSW systems. Generally, decision alternatives with lower system cost would be obtained if the environmental requirement was less strict; however, this may lead to a higher system failure risk. On the contrary, a more costly management scheme would ensure the environmental constraints be satisfied with a higher degree of reliability. The proposed model could assist decision makers in identifying effective waste allocation patterns and expansion options, with both cost and risk information being considered under complex uncertainties. TFCMP is also applicable to other management fields and its function could be extended through coupling with other inexact optimization methods.