An improved Stud Genetic Algorithm using the Opposition-based Strategy
Available Online April 2016.
- 10.2991/ameii-16.2016.6How to use a DOI?
- Opposition-based Strategy, Stud Genetic Algorithm, Optimization Algorithm
This paper proposed an improved Stud Genetic Algorithm using the Opposition-based strategy (SGAO) to improve the performance of the traditional SGA and accelerate its convergence speed. In SGAO, we use opposition-based approach to initialize the population and to perform mutation with the aim to improve the quality of solutions. In experiments, we use some benchmark functions to the show the performance of the proposed approach and compare it with other algorithms such as genetic algorithm, different evolutionary, particle swarm optimization and stud genetic algorithm. Results show that SGAO has faster convergence speed and higher solution precision.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Hongwei Xu PY - 2016/04 DA - 2016/04 TI - An improved Stud Genetic Algorithm using the Opposition-based Strategy BT - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016) PB - Atlantis Press SP - 32 EP - 37 SN - 2352-5401 UR - https://doi.org/10.2991/ameii-16.2016.6 DO - 10.2991/ameii-16.2016.6 ID - Xu2016/04 ER -