Municipal solid waste allocation planning using interval programming

• Main Author: Li, Chengxi.
• Other Authors: School of Civil and Environmental Engineering
• Format: Final Year Project
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Environmental engineering::Waste management
• Online Access: http://hdl.handle.net/10356/52877
• Institution: Nanyang Technological University

The provision of a reliable, feasible and sustainable municipal solid waste (MSW) management plan is essential in ensuring public health and standard of living. However, the presence of multiple parameter uncertainties within the complex network of MSW elements has been a challenge to produce reliable conclusions for decision-making. An interval mixed-integer linear programming (IMILP) model was developed in this study to optimise system cost of a MSW management system. The model improved upon the existing deterministic mixed-integer linear programming (DMILP) by allowing uncertainties in the input parameters to be expressed as discrete intervals, when parameter distributions were unknown or difficult to ascertain. The integration of mixed-integer programming (MIP) allowed the model to deal with capacity expansion decisions in various management facilities. The model was applied to three policy scenarios in Foshan, China. The IMILP model illustrated a clear shift of preference from landfilling to incineration and composting, when policy goals became stricter. There was also significant uncertainty in capacities expansions that might lead to large excess capacities. The highest cost corresponded to the strictest scenario and was most sensitive to three parameters: unit transportation cost, waste generation rate and residue rate of composting. A policy scenario with moderate regulation and financial burden was recommended. It is suggested that IMILP to be integrated with chance-constrained mixed-integer linear programming (CCMILP) model in a further study of the case. This would enable planners to obtain interval solutions associated with different constraint violation risks, thereby able to evaluate system failure risk against system cost. Nonetheless, the interval solutions obtained in this study would provide planners with considerable flexibility in choosing decision alternatives that would best suit the economic, social, technological and political considerations of the city.