Long-term panning of waste diversion under interval and probabilistic uncertainties

Abstract

An inexact chance-constraint mixed integer linear programming (ICMILP) model was proposed for supporting long-term planning of waste management in the City of Foshan, China. The presented model took waste generation, collection, transportation and treatment processes into consideration, and was specifically designed to reflect the practical situations of waste management in Chinese cities. Three special characteristics of the developed method made it unique compared with the other optimization techniques that deal with uncertainties. Firstly, it provided a linkage to pre-regulated policies that had to be respected when a modeling effort was undertaken; secondly, it was useful for tackling uncertainties presented as intervals probabilities; thirdly, it could facilitate dynamic analysis for decisions of facility expansions within a multi-facility, multi-period, multi-level, and multi-option context. Three scenarios were considered based on various combinations of financial capability and environmental demand. The results indicate that the city would attain a relatively low diversion rate if its waste management practices continue to be based on the existing policy over 15 years. However, higher diversion rates associated with lower system cost would be achieved if the City's policy is to be based on an aggressive capacity-expansion plan for composting and incinerating facilities. The model solutions would be valuable for supporting the long-term capacity planning for waste-management facilities as well as the formulation of policies regarding waste generation, diversion and management.