Interactive Evolutionary Computation algorithms applied to solve Rastrigin test functions

  • Yago Saez
  • Pedro Isasi
  • Javier Segovia
Part of the Advances in Soft Computing book series (AINSC, volume 29)


this paper presents a new approach to interactive evolutionary computation that helps the user in the difficult task of finding an optimal solution between multiple possibilities. There are several ways of applying algorithms in interactive evolutionary computation; in this paper we explain three of them in order to make an experimental comparative study. Proceeding with a main goal of solving complex problems as fast as possible, we take the Rastrigin test function as a benchmark and it is executed with the three algorithms described. The aim is to show clearly the results of the algorithms in terms of solution quality and number of iterations. The results clearly show that the use of the proposed method based on chromosome learning heuristics works well even for non Interactive Evolutionary Computation frameworks.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yago Saez
    • 1
  • Pedro Isasi
    • 1
  • Javier Segovia
    • 2
  1. 1.Department of Artificial IntelligenceUniversity Carlos III of MadridMadrid
  2. 2.Systems and Languages department, Faculty of Computer ScienceUniversity Politécnica of MadridMadrid

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