A New Multi Objective Mathematical Model for Relief Distribution Location at Natural Disaster Response Phase

TL;DR

This paper develops a multi-objective mathematical model for relief distribution during natural disasters, utilizing meta-heuristic algorithms like EC and NSGA II to efficiently solve large-scale problems with multiple objectives.

Contribution

It introduces a new multi-objective model for disaster relief location and applies advanced evolutionary algorithms to solve complex, large-scale problems efficiently.

Findings

Meta-heuristic algorithms effectively solve large-scale relief distribution problems.

The model considers multiple objectives and complex time calculations.

NSGA II provides near-optimal solutions in less computational time.

Abstract

Every year, natural disasters such as earthquake, flood, hurricane and etc. impose immense financial and humane losses on governments owing to their unpredictable character and arise of emergency situations and consequently the reduction of the abilities due to serious damages to infrastructures, increases demand for logistic services and supplies. First, in this study the necessity of paying attention to locating procedures in emergency situations is pointed out and an outline for the studied case of disaster relief supply chain was discussed and the problem was validated at small scale. On the other hand, to solve this kind of problems involving three objective functions and complicated time calculation, meta-heuristic methods which yield almost optimum solutions in less time are applied. The EC method and NSGA II algorithm are among the evolutionary multi-objective optimization algorithms applied in this case. In this study the aforementioned algorithm is used for solving problems at large scale.