실수 코딩 유전자 알고리즘을 이용한 생산 시스템의 시뮬레이션 최적화

• 영문명: Simulation Optimization of Manufacturing System using Real - coded Genetic Algorithm
• 발행기관: 한국산업경영시스템학회
• 저자명: 박경종(Kyoung-Jong Park)
• 간행물 정보: 『산업경영시스템학회지』제28권 제3호, 149~155쪽, 전체 7쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2005.09.01

영문 초록

In this paper, we optimize simulation model of a manufacturing system using the real-coded genetic algorithm. Because the manufacturing system expressed by simulation model has stochastic process, the objective functions such as the throughput of a manufacturing system or the resource utilization are not optimized by simulation itself. So, in order to solve it, we apply optimization methods such as a genetic algorithm to simulation method. Especially, the genetic algorithm is known to more effective method than other methods to find global optimum, because the genetic algorithm uses entity pools to find the optimum. In this study, therefore, we apply the real-coded genetic algorithm to simulation optimization of a manufacturing system, which is known to more effective method than the binary-coded genetic algorithm when we optimize the constraint problems. We use the reproduction operator of the applied real-coded genetic algorithm as technique of the remainder stochastic sample with replacement and the crossover operator as the technique of simple crossover. Also, we use the mutation operator as the technique of the dynamic mutation that configures the searching area with generations.

목차

Abstract

1. 서론

2. 시뮬레이션 모델

3. 실수코딩 유전자 알고리즘

4. 실험 및 분석

5. 결론

참고문헌