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Landfill space consumption dynamics in the Lower Rio Grande Valley by grey integer programming-based games
Eric Davila1, Ni-Bin Chang, Syamala Diwakaruni
1Department of Environmental Engineering, Texas A&M University-Kingsville, 917 W. Ave., Engineering Complex 367, Kingsville, TX 78363, USA.
Journal of Environmental Management
|April 28, 2005
Summary
Solid waste management in the Lower Rio Grande Valley faces challenges from population growth. Grey integer programming and game theory offer strategies for landfills to optimize pricing and secure waste contracts.
Area of Science:
- Operations Research
- Environmental Management
- Game Theory
Background:
- The Lower Rio Grande Valley (LRGV) region's growth, spurred by NAFTA, has led to a significant increase in solid waste generation.
- A 39.8% population increase over 10 years resulted in a 25% rise in per capita solid waste disposal, creating a landfill space shortage.
Purpose of the Study:
- To develop optimal management and pricing strategies for landfill operators in a competitive market.
- To address the need for efficient solid waste pattern distribution and minimize net costs for municipalities.
Main Methods:
- Utilized a grey integer programming algorithm to model uncertainty in the solid waste system and optimize distribution.
- Employed game theoretic analysis with grey integer submodels to construct payoff matrices for competitive pricing strategies.
Main Results:
- Identified optimal pricing tactics, termed 'grey Nash equilibria,' through a two-tiered analysis.
- Demonstrated that these strategies can help landfills, like the City of Edinburg landfill, maintain waste contracts amidst competition.
Conclusions:
- Grey integer programming-based game theory provides a robust framework for landfill pricing strategies.
- This approach can effectively manage ambiguity in waste generation, capacity, and shipping costs for competitive advantage.