Chapter

Analysis and Design of Intelligent Systems using Soft Computing Techniques

Volume 41 of the series Advances in Soft Computing pp 473-481

Providing Intelligence to Evolutionary Computational Methods

  • Oscar MontielAffiliated withCentro de Investigación y Desarrollo de Tecnología Digital del Instituto, Politécnico Nacional (CITEDI-IPN) Av. del Parque No. 1310, Mesa de, Otay, Tijuana, B.C.
  • , Oscar CastilloAffiliated withDepartment of Computer Science, Tijuana Institute of Technology P.O. Box 4207, Chula Vista CA 91909
  • , Patricia MelinAffiliated withDepartment of Computer Science, Tijuana Institute of Technology P.O. Box 4207, Chula Vista CA 91909
  • , Roberto SepúlvedaAffiliated withCentro de Investigación y Desarrollo de Tecnología Digital del Instituto, Politécnico Nacional (CITEDI-IPN) Av. del Parque No. 1310, Mesa de, Otay, Tijuana, B.C.

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Abstract

It is presented an intelligent evolutionary method to solve single objective optimization problems, we called this method Single Objective Intelligent Evolutionary Algorithm (SO-IEA). This method uses several mechanisms that work synergistically to provide the optimal solution by handling in an intelligent way, the number of times that the objective function needs to be evaluated. The SO-IEA was subjected to several tests using complex benchmark functions and the results were statistically compared to other state of the art evolutionary algorithms (EA) obtaining that the SO-IEA outperformed in time and in precision the other methods. In general, the ideas presented here can be easily adapted to other EAs.