Intelligent modeling method based on genetic algorithm for partner selection in virtual organizations

The goal of a Virtual Organization is to find the most appropriate partners in terms of expertise, cost wise, quick response, and environment. In this study we propose a model and a solution approach to a partner selection problem considering three main evaluation criteria: cost, time and risk. This multiobjective problem is solved by an improved GA that includes meiosis specific characteristics and step-size adaptation for the mutation operator. The algorithm performs strong exploration initially and exploitation in later generations. It has high global search ability and a fast convergence rate and also avoids premature convergence. On the basis of the numerical investigations, the incorporation of the proposed enhancements has been successfully proved.


Issue Date:
2011-04
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/204193
Published in:
Business and Economic Horizons, Volume 05, Issue 2
Business and Economic Horizons
Page range:
23-34
Total Pages:
12
JEL Codes:
C61; C63; M21
Series Statement:
5
3




 Record created 2017-04-01, last modified 2017-05-02

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