Siting and routing assessment for solid waste management under uncertainty using the grey mini-max regret criterion

Area of Science:

• Environmental Science
• Operations Research
• Regional Planning

Background:

• Solid waste management (SWM) presents significant environmental challenges in the rapidly urbanizing Lower Rio Grande Valley (LRGV).
• Decision-making in SWM is often hampered by vague data, ambiguity, and uncertainty regarding key factors.
• Existing landfill space is diminishing, necessitating innovative solutions for waste disposal and infrastructure development.

Purpose of the Study:

• To develop and apply an innovative optimization model for regional SWM planning under uncertain conditions.
• To outline an optimal strategy for solid waste routing and the potential construction of landfills or incinerators in the LRGV.
• To provide decision-makers with a robust framework for addressing data scarcity and decision-making vagueness in SWM.

Main Methods:

• Implementation of a grey mini-max regret (GMMR) integer programming algorithm.
• Application of the GMMR model to a case study in the Lower Rio Grande Valley, Texas.
• Analysis of waste routing and facility siting options within a defined planning horizon (2005-2010).

Main Results:

• The GMMR model successfully generated hedged sets of options that account for various uncertainties.
• The model facilitated insightful scenario planning, capable of handling situational and data-driven uncertainty.
• Incineration facilities were found to be less competitive than landfills due to high capital investment, though public-private partnerships could be viable.

Conclusions:

• The GMMR model offers a novel approach to SWM planning, enhancing decision-making under uncertainty.
• The study provides valuable insights for efficient waste routing and facility siting in the LRGV.
• Findings suggest that landfill development remains a more economically feasible option for municipalities compared to incineration.