Applying network flow optimisation techniques to minimise cost associated with flood disaster

Area of Science:

• Operations Research
• Disaster Management
• Logistics

Background:

• Flooding disasters pose significant challenges globally, necessitating efficient humanitarian aid distribution.
• Coordinating rescue operations requires minimizing costs while meeting diverse needs.

Purpose of the Study:

• To develop and apply a mathematical model for minimizing the cost of emergency rescue operations during flooding disasters.
• To optimize the distribution of relief materials from supply depots to distribution points.

Main Methods:

• Utilized stochastic programming for a multicommodity and multimodel network flow problem.
• Incorporated four supply depots, six distribution points, two vehicle types (helicopters and trucks), and three relief material types (food, water, medical).
• Modeled three disaster scenarios (mild, medium, severe) with associated probabilities and solved using LINGO software.

Main Results:

• The formulated model effectively reduced distribution costs for emergency rescue operations.
• Achieved a minimized cost of approximately $1,016,673.37 for successful rescue operations.
• Demonstrated a minimal difference between demand and met demand, indicating efficient resource allocation.

Conclusions:

• The developed model provides a benchmark cost for governments and agencies planning disaster response.
• Integrating air and road transport modes optimizes delivery times, ultimately saving lives.