Optimization by Hybridization of a Genetic Algorithm with the PROMOTHEE Method: Management of Multicriteria Localization
Myriem Alijo, Otman Abdoun, Mostafa Bachran, Amal Bergam

TL;DR
This paper presents a hybrid optimization approach combining genetic algorithms, economic intelligence, and multicriteria analysis, specifically using PROMETHEE, to improve decision-making in territorial localization for economic activities.
Contribution
It introduces a novel hybrid model integrating genetic algorithms with PROMETHEE and economic intelligence for multicriteria localization decisions.
Findings
Enhanced decision quality for territorial localization.
Effective mapping of favorable regions using the hybrid model.
Improved compromise solutions between conflicting criteria.
Abstract
The decision to locate an economic activity of one or several countries is made taking into account numerous parameters and criteria. Several studies have been carried out in this field, but they generally use information in a reduced context. The majority are based solely on parameters, using traditional methods which often lead to unsatisfactory solutions.This work consists in hybridizing through genetic algorithms, economic intelligence (EI) and multicriteria analysis methods (MCA) to improve the decisions of territorial localization. The purpose is to lead the company to locate its activity in the place that would allow it a competitive advantage. This work also consists of identifying all the parameters that can influence the decision of the economic actors and equipping them with tools using all the national and international data available to lead to a mapping of countries,…
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Taxonomy
TopicsGlobal Trade and Competitiveness
