Siting and routing assessment for solid waste management under uncertainty using the grey mini-max regret criterion.
Solid waste management (SWM) is at the forefront of environmental concerns in the Lower Rio Grande Valley (LRGV), South Texas. The complexity in SWM drives area decision makers to look for innovative and forward-looking solutions to address various waste management options. In decision analysis, it is not uncommon for decision makers to go by an option that may minimize the maximum regret when some determinant factors are vague, ambiguous, or unclear. This article presents an innovative optimization model using the grey mini-max regret (GMMR) integer programming algorithm to outline an optimal regional coordination of solid waste routing and possible landfill/incinerator construction under an uncertain environment. The LRGV is an ideal location to apply the GMMR model for SWM planning because of its constant urban expansion, dwindling landfill space, and insufficient data availability signifying the planning uncertainty combined with vagueness in decision-making. The results give local decision makers hedged sets of options that consider various forms of systematic and event-based uncertainty. By extending the dimension of decision-making, this may lead to identifying a variety of beneficial solutions with efficient waste routing and facility siting for the time frame of 2005 through 2010 in LRGV. The results show the ability of the GMMR model to open insightful scenario planning that can handle situational and data-driven uncertainty in a way that was previously unavailable. Research findings also indicate that the large capital investment of incineration facilities makes such an option less competitive among municipal options for landfills. It is evident that the investment from a municipal standpoint is out of the question, but possible public-private partnerships may alleviate this obstacle.
Chang
Ni-Bin
NB
Department of Civil and Environmental Engineering, University of Central Florida, Orlando, Florida 32816, USA. nchang@mail.ucf.edu
Davila
Eric
E
D003198:Computer Simulation; D003247:Conservation of Natural Resources / Q000379:methods; D008962:Models, Theoretical; D010934:Planning Techniques; D012037:Refuse Disposal / Q000379:methods* / Q000706:statistics & numerical data; D018505:Waste Management / Q000191:economics / Q000379:methods* / Q000706:statistics & numerical data