Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Proportional-Integral-Derivative Evaluation for Enhancing Performance of Genetic Algorithms

유전자 알고리즘의 성능향상을 위한 비례-적분-미분 평가방법

  • Published : 2003.08.01
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Abstract

This paper proposes a proportional-integral-derivative (PID) evaluation method for enhancing performance of genetic algorithms. In PID evaluation, the fitness of individuals is evaluated by not only the fitness derived from an evaluation function, but also the parents fitness of each individual and the minimum and maximum fitness from initial generation to previous generation. This evaluation decreases the probability that the genetic algorithms fall into a premature convergence phenomenon and results in enhancing the performance of genetic algorithms. We experimented our evaluation method with typical numerical function optimization problems. It was found from extensive experiments that out evaluation method can increase the performance of genetic algorithms greatly. This evaluation method can be easily applied to the other types of genetic algorithms for improving their performance.

본 논문에서는 유전자 알고리즘의 성능향상을 위한 비례-적분-미분 평가방법을 제안한다. 비례-적분-미분 평가방법에서는 평가함수에 의하여 계산된 적합도와 더불어 각 개체의 부모 적합도, 초기세대로부터 이전세대까지의 최소, 최대 적합도를 이용하여 평가함으로서 유전자 알고리즘의 성능저하를 가져오는 조숙수렴 (premature convergence) 확률을 줄여주어 결과적으로 유전자 알고리즘의 성능을 향상시키게 된다. 비례-적분-미분 평가방법의 성능을 보이기 위하여 유전자 알고리즘 성능 검증에 많이 사용되어온 대표적인 함수 최적화 문제들을 적용하여 실험해본 결과 제안한 방법이 유전자 알고리즘의 성능을 크게 향상 시킬 수 있음을 확인하였다. 제안한 평가방법은 다른 형태의 유전자 알고리즘의 성능향상을 위해서도 쉽게 적용될수 있다.

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