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An inexact two-stage mixed integer linear programming method for solid waste management in the City of Regina
1Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, SK, Canada.
Journal of Environmental Management
|May 9, 2006
Summary
This study introduces an interval-parameter two-stage mixed integer linear programming (ITMILP) model for robust waste management planning. The model effectively handles uncertainty, optimizing waste diversion and landfill use for long-term sustainability.
Area of Science:
- Operations Research
- Environmental Engineering
- Waste Management
Background:
- Solid waste management systems face dynamic, interactive, and uncertain characteristics.
- Long-term planning requires addressing waste diversion and landfill capacity.
- Existing models may not adequately capture probabilistic and interval-based uncertainties.
Purpose of the Study:
- To develop an interval-parameter two-stage mixed integer linear programming (ITMILP) model.
- To support long-term waste management planning in the City of Regina.
- To incorporate both stochastic and interval uncertainties into a unified framework.
Main Methods:
- Development of an interval-parameter two-stage mixed integer linear programming (ITMILP) model.
- Integration of two-stage stochastic programming and interval linear programming.
- Application to solid waste management planning considering dynamic and uncertain factors.
Main Results:
- The ITMILP model successfully generated reasonable solutions for waste management planning.
- The model effectively addressed uncertainties in waste generation and management.
- Solutions provided valuable insights for waste flow allocation and landfill capacity planning.
Conclusions:
- The developed ITMILP model is a valuable tool for long-term waste management planning.
- The model supports informed decision-making regarding waste diversion and landfill strategies.
- Findings aid in formulating effective local policies and regulations for waste management.
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