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Two phase algorithm for bi-objective relief distribution location problem.

Mamta Mishra¹, Surya Prakash Singh¹, Manmohan Prasad Gupta¹

¹Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India.

Annals of Operations Research

|June 22, 2022

Summary

This summary is machine-generated.

This study introduces a two-stage model for planning relief distribution centers (DCs) to minimize costs and improve disaster response. A novel two-phase algorithm proved more efficient than traditional methods for optimal DC location.

Keywords:

Heuristic Location problem NP-hard problem Relief distribution

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Area of Science:

Operations Research
Humanitarian Logistics
Disaster Management

Background:

Effective relief distribution center (DC) location is critical for timely disaster response and victim support.
Existing facility location models often lack the complexity to address real-world humanitarian logistics constraints.

Purpose of the Study:

To propose a two-stage model for optimizing relief distribution center (DC) location planning.
To develop and evaluate a novel two-phase algorithm for solving this complex problem efficiently.

Main Methods:

A two-stage optimization model was formulated to determine the minimum number and optimal locations of relief DCs.
A novel two-phase algorithm, featuring exploration and exploitation phases, was developed to solve the NP-hard location problem.
The proposed algorithm was computationally compared against established methods like genetic algorithms and pattern search.

Main Results:

The proposed two-phase algorithm demonstrated superior efficiency and effectiveness compared to conventional metaheuristic methods.
The algorithm successfully identified near-optimal solutions and enhanced solution quality through proximity investigation.
Comparative analysis confirmed the algorithm's performance across various data set sizes.

Conclusions:

The developed two-stage model and novel algorithm offer an effective solution for humanitarian logistics location planning.
The findings highlight the potential for improved disaster response through optimized relief distribution networks.
The proposed approach provides a robust and efficient tool for humanitarian aid organizations.