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Identifying optimal regional solid waste management strategies through an inexact integer programming model
Li He1, Guo-He Huang, Guang-Ming Zeng
1Faculty of Engineering, University of Regina, Regina, Saskachewan, Canada S4S 0A2.
Waste Management (New York, N.Y.)
|April 15, 2008
Summary
A new inexact mixed-integer bi-infinite programming (IMIBIP) method handles infinite objectives and constraints. This approach offers reasonable solutions for waste management capacity planning, balancing cost and reliability.
Area of Science:
- Operations Research
- Environmental Engineering
- Optimization
Background:
- Existing inexact mixed-integer linear programming (IMILP) methods are limited to crisp intervals.
- Current inexact mixed-integer semi-infinite programming (IMISIP) methods handle only single-objective problems with infinite constraints.
Purpose of the Study:
- To propose an inexact mixed-integer bi-infinite programming (IMIBIP) method.
- To address inexact programming problems with both infinite objectives and constraints.
- To apply the IMIBIP method to waste management capacity planning under uncertainty.
Main Methods:
- Incorporation of functional intervals into the programming framework.
- Development of the IMIBIP method to handle dual infinities in objectives and constraints.
- Application and comparison with IMILP in capacity planning scenarios.
Main Results:
- The IMIBIP method generates reasonable solutions for waste management capacity planning.
- IMIBIP solutions reflect higher system costs due to market factor fluctuations.
- IMILP solutions show higher system reliability and lower constraint violation risk.
Conclusions:
- IMIBIP offers a robust framework for complex optimization problems with dual infinities.
- The trade-off between cost and reliability is highlighted in waste management capacity planning.
- IMIBIP provides a valuable tool for decision-making under uncertainty in environmental systems.
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