An evolving fuzzy-neural rule with slack diversification is proposed in the present work to improve the performance of job dispatching in a wafer fabrication factory. The evolving fuzzy-neural rule is a modification from the two-factor tailored nonlinear fluctuation smoothing rule for mean cycle time (2f-TNFSMCT) by diversifying the slack values of jobs to be dispatched dynamically, which has been shown to be conducive to the performance in several previous studies. After evaluation of the proposed rule, some evidence was gained to support its effectiveness. Based on the findings in this research we also derived several directions that can be exploited in the future.
목차
Abstract 1. Introduction 2. Methodology 3. A Simulation Study 4. Conclusions and Directions for Future Research Acknowledgements References
보안공학연구지원센터(IJGDC) [Science & Engineering Research Support Center, Republic of Korea(IJGDC)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Grid and Distributed Computing
간기
격월간
pISSN
2005-4262
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Grid and Distributed Computing Vol.5 No.2