원문정보
보안공학연구지원센터(IJSIP)
International Journal of Signal Processing, Image Processing and Pattern Recognition
Vol.9 No.3
2016.03
pp.231-238
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In order to improve the convergence and diversity of multiobjective optimization algorithms, the harmonic average distance is employed to improve the aggregating function combined L-rank value. Selection model and searching scheme of artificial bee colony algorithm and diversity maintaining scheme are improved in this paper. This novel many objectives optimization method based on improved artificial bee colony algorithm (ABC) in this paper is compared with other three many objectives optimization methods on 3 to 8 objectives DTLZ. Simulation results show that the proposed algorithm is superior to other algorithms in the diversity and convergence of solutions.
목차
Abstract
1. Introduction
2. Improved Methods in ABC
2.1. Improved Fitness Evaluation Method
2.2. Improved Selection Mode of Onlookers
2.3. Forced Mutation Operation of the Employed Bee
2.4. Diversity Maintaining Scheme
3. Steps of the Proposed Algorithm
4. Experimental Results
5. Conclusions
Acknowledgements
References
1. Introduction
2. Improved Methods in ABC
2.1. Improved Fitness Evaluation Method
2.2. Improved Selection Mode of Onlookers
2.3. Forced Mutation Operation of the Employed Bee
2.4. Diversity Maintaining Scheme
3. Steps of the Proposed Algorithm
4. Experimental Results
5. Conclusions
Acknowledgements
References
키워드
저자정보
참고문헌
자료제공 : 네이버학술정보