An Efficient Method for Nonlinear Optimization Problems using Genetic Algorithms

유전해법을 이용한 비선형최적화 문제의 효율적인 해법

  • 임승환 (경북 외국어 전문대학 국제통상과) ;
  • 이동춘 (동아대학교 산업공학과)
  • Published : 1997.11.01

Abstract

This paper describes the application of Genetic Algorithms(GAs) to nonlinear constrained mixed optimization problems. Genetic Algorithms are combinatorial in nature, and therefore are computationally suitable for treating discrete and integer design variables. But, several problems that conventional GAs are ill defined are application of penalty function that can be adapted to transform a constrained optimization problem into an unconstrained one and premature convergence of solution. Thus, we developed an improved GAs to solve this problems, and two examples are given to demonstrate the effectiveness of the methodology developed in this paper.

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