Academic journal article Iranian Journal of Public Health

Development a Heuristic Method to Locate and Allocate the Medical Centers to Minimize the Earthquake Relief Operation Time

Academic journal article Iranian Journal of Public Health

Development a Heuristic Method to Locate and Allocate the Medical Centers to Minimize the Earthquake Relief Operation Time

Article excerpt

Abstract

Background: Location-allocation is a combinatorial optimization problem, and is defined as Non deterministic Polynomial Hard (NP) hard optimization. Therefore, solution of such a problem should be shifted from exact to heuristic or Meta heuristic due to the complexity of the problem. Locating medical centers and allocating injuries of an earthquake to them has high importance in earthquake disaster management so that developing a proper method will reduce the time of relief operation and will consequently decrease the number of fatalities.

Methods: This paper presents the development of a heuristic method based on two nested genetic algorithms to optimize this location allocation problem by using the abilities of Geographic Information System (GIS). In the proposed method, outer genetic algorithm is applied to the location part of the problem and inner genetic algorithm is used to optimize the resource allocation.

Results: The final outcome of implemented method includes the spatial location of new required medical centers. The method also calculates that how many of the injuries at each demanding point should be taken to any of the existing and new medical centers as well.

Conclusions: The results of proposed method showed high performance of designed structure to solve a capacitated location-allocation problem that may arise in a disaster situation when injured people has to be taken to medical centers in a reasonable time.

Keywords: Location-allocation, Optimization, Medical center

(ProQuest: ... denotes formulae omitted.)

Introduction

The location-allocation problem belongs to NP-HARD problems which get complicated exponen-tially by the increase of the number of service cen-ters and customers. As a consequent, the exact and mathematical techniques cannot be applied in many cases, so the proper heuristic methods should be utilized depending on their structures and topics. Li and Yeh (1) classified most of the location- allocation problems as NP hard optimization. If the problem is NP hard, solution of that problem should be shifted from exact to heuristic or Meta heuristic due to complexity of the problem, so meta heuristic solution like ge-netic algorithm have been exploited to solve loca-tion-allocation problem (2). Since majority part of data and analyses applied in the location-allocation problems are spatially reference, GIScience's abili-ties can be utilized beside optimization methods, simulations and different allocation analyses for better solving these problems (3).

Researches reveal that time is a vital element in reduction of casualty after the earthquake, as the first 24 hours is the most significant time for saving victims, because the possibility of surviving is higher for the victims in these hours (4). Previous studies showed that one of the major medical problems in casualties like earthquake is from delayed medical care (5); therefore the reduction of rescue operation will decrease number of fatalities. One part of this operation is to allocate victims to different medical centers in minimum time. So, development of an appropriate method for optimizing the process of allocating victims to several existent medical centers can help lessen the casualties of an earthquake. Developed models for resource allocation of relief operations can be classified into two different categories of rescue and transport casualties after disaster, and logistics problems to deliver supplies into the disaster-affected areas. While so far, some researchers have worked on resources allocation in relief operations in natural disasters (6-8), other researchers have established some models on logistics problems to deliver supplies into the disaster-affected areas (9, 10).

Despite the significant number of works carried out in the literature, very few researches have been performed in Iran to employ the GIS techniques and artificial intelligence methods for disaster management. …

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