An integrated multi-objective model for disaster waste clean-up systems optimization

Post-disaster waste clean-up systems are complex and expensive operations that need to consider multiple stakeholders with different objectives. We propose a mixed-integer programming model that models the waste clean-up operations as a two-echelon system. The model decides on the location of waste processing facilities, the use of demolition resources, and the number and type of vehicles to be assigned to each echelon at each time slot of the planning horizon. The objectives considered in the model include minimizing environmental impacts, economic costs, and total time spent on the operations. Numerical results obtained on a case study based on the '2009 Victoria Black Saturday Bush-fires' case and on synthetically generated instances are used to obtain Pareto frontiers. The research concludes that the three objectives considered are indeed conflictive, and the explicit consideration of each goal can help decision-makers find the best trade-off solutions.

Automated summary

This study proposes a mixed-integer programming model for post-disaster waste clean-up systems, taking into account multiple stakeholders and objectives. Numerical results confirm the conflicting nature of the objectives considered and highlight the importance of explicitly considering each goal to find the best trade-off solutions.