OPERATIONS RESEARCH MODELS FOR MUNICIPAL WASTE MANAGEMENT SYSTEMS DESIGN

Abstract

Waste management continues to be a critical issue of national priority in many developing and developed countries. This thesis presents advances in municipal waste management systems design using state of the art operations research methodologies. Firstly, we develop a two-stage stochastic programming model for the economic feasibility analysis and design of a hybrid waste treatment system, when the input waste streams and technical parameters are uncertain. Secondly, we develop a non-linear programming and agent-based modelling framework to analyze the utilization of market mechanism for sustaining a decentralized waste management with private sector competition. Lastly, we propose an integrated waste sorting and treatment location planning model by applying both stochastic and robust programming approach to hedge against waste composition ambiguity issue raised from waste sorting operations. The key contribution of all these works is to help regulators design municipal waste management systems in an economically feasible and sustainable manner.