An interval-based regret-analysis method for identifying long-term municipal solid waste management policy under...

Area of Science:

• Environmental Engineering
• Operations Research
• Decision Science

Background:

• Municipal solid waste (MSW) management requires robust long-term planning strategies.
• Uncertainty in system costs and risk levels complicates decision-making for MSW management.
• Existing models may not adequately address uncertainties expressed as interval values and random variables.

Purpose of the Study:

• To develop and apply an interval-based regret-analysis (IBRA) model for long-term MSW management planning.
• To support decision-making in the City of Changchun, China.
• To provide a framework that accounts for uncertainties without assuming probabilistic distributions.

Main Methods:

• Developed an interval-based regret-analysis (IBRA) model.
• Integrated interval-parameter programming (IPP) and minimax-regret (MMR) analysis within an integer programming framework.
• Generated an interval regret matrix using interval system costs and applied the interval minimax regret (IMMR) criterion.

Main Results:

• The IBRA model successfully generated reasonable solutions for long-term MSW management planning.
• The model accounts for economic consequences across various scenarios, system costs, and risk levels.
• Decision alternatives were identified based on the interval minimax regret (IMMR) criterion.

Conclusions:

• The developed IBRA model provides a valuable tool for strategic MSW management planning.
• The model facilitates a compromise between minimizing system costs and system-failure risk.
• The approach is effective in handling uncertainties inherent in MSW management decision-making.