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Constrained Optimization Using Organizational Evolutionary Algorithm

  • Jing Liu
  • Weicai Zhong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4247)

Abstract

This paper designs a new kind of structured population and evolutionary operators to form a novel algorithm, Organizational Evolutionary Algorithm (OEA), for solving constrained optimization problems. A simple and non problem-dependent technique is incorporated into OEA to handle the constraints. In OEA, a population consists of organizations, and an organization consists of individuals. All evolutionary operators are designed to simulate the interaction among organizations. In experiments, 4 well-studied engineering design problems are used to test the performance of OEA. The results show that OEA obtains good results both in the solution quality and the computational cost.

Keywords

Evolutionary algorithms organization constrained optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jing Liu
    • 1
  • Weicai Zhong
    • 1
  1. 1.Institute of Intelligent Information ProcessingXidian UniversityXi’anChina

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