Volume 2, Issue 1, June 2015, Pages 1 - 4
Analysis of Asymmetric Mutation Model in Random Local Search
Hiroshi Furutani, Makoto Sakamoto, Yifei Du, Kenji Aoki
Available Online 1 June 2015.
- 10.2991/jrnal.2015.2.1.1How to use a DOI?
- Random Local Search, Asymmetric mutation, Hitting time, Markov chain
In a standard Evolutionary Algorithms (EAs), one uses the same rate for mutations from bit 1 to bit 0 and its reverse direction. There are many reports that the asymmetric mutation model is a very powerful strategy in EAs to obtain better solutions more efficiently. In this paper, we report stochastic behaviors of algorithms that are asymmetric mutation models of Random Local Search (RLS). The mathematical structure of asymmetry model can be derived in terms of a finite Markov chain. We demonstrate some useful results representing the effects of asymmetric mutation.
- © 2013, 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 - JOUR AU - Hiroshi Furutani AU - Makoto Sakamoto AU - Yifei Du AU - Kenji Aoki PY - 2015 DA - 2015/06/01 TI - Analysis of Asymmetric Mutation Model in Random Local Search JO - Journal of Robotics, Networking and Artificial Life SP - 1 EP - 4 VL - 2 IS - 1 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.2015.2.1.1 DO - 10.2991/jrnal.2015.2.1.1 ID - Furutani2015 ER -