Optimisation of waste clean-up after large-scale disasters

Area of Science:

• Disaster Management
• Environmental Engineering
• Operations Research

Background:

• Disaster waste clean-up is crucial for recovery and restoring normal functions.
• Effective management of waste post-disaster requires efficient logistics and processing.

Purpose of the Study:

• To develop a model for optimizing disaster waste clean-up operations.
• To minimize both the total cost and time involved in disaster waste management.

Main Methods:

• A multi-objective mixed integer programming model was formulated.
• The model incorporates demolition, collection, processing, and transportation phases.
• Three solution approaches were developed and tested.

Main Results:

• The developed models provide near-optimal solutions within practical timeframes.
• Artificial instances demonstrated the models' efficiency.
• A real case study showed the models' applicability for decision-making.

Conclusions:

• The study offers a robust framework for disaster waste clean-up optimization.
• Effective site selection for temporary disaster waste management sites (TDWMSs) and scheduling are key.
• The research facilitates minimized cost and time in disaster recovery efforts.