An interval-parameter stochastic robust optimization model for supporting municipal solid waste management under uncertainty

Abstract

A stochastic robust interval linear programming model (IPRO) was developed for supporting municipal solid waste management under uncertainty. The model improves upon the existing stochastic robust optimization (SRO) and interval linear programming (ILP) methods by allowing evaluations of trade-offs among expected costs, cost variability, and risk of violating relax constraints simultaneously, as well as reflections of complex uncertainties through both interval and stochastic theories. A long-term waste management problem was used to demonstrate the applicability of IPRO model. The results indicated that IPRO normally led to interval solutions, where waste-management alternatives could be generated by adjusting the decision-variable values within their intervals. The model could also help waste managers to identify desired policies that under various environmental, economic, system-feasibility and system-reliability constraints.