Bali , Kavitesh and Chandra, Rohitash (2015) Multi - island competitive cooperative coevolution for real parameter global optimization. In: Neural Information Processing. Lecture Notes in Computer Science, 9491 . Springer International Publishing, Istanbul, Turkey , pp. 127-136. ISBN 978-3-319-26554-4
Preview |
PDF
- Published Version
Download (231kB) | Preview |
Abstract
Problem decomposition is an important attribute of cooperative coevolution that depends on the nature of the problems in terms of separability which is defined by the level of interaction amongst decision variables. Recent work in cooperative coevolution featured competition and collaboration of problem decomposition methods that was implemented as islands in a method known as competitive island cooperative coevolution (CICC). In this paper, a multi-island competitive cooperative coevolution algorithm (MICCC) is proposed in which several different problem decomposition strategies are given a chance to compete,
collaborate and motivate other islands while converging to a common solution.
The performance of MICCC is evaluated on eight different benchmark functions
and are compared with CICC where only two islands were utilized. The results from the experimental analysis show
that competition and collaboration of several different island can yield solutions with a quality better than
the two-island competition algorithm (CICC) on most
complex multi-modal problems.
| Item Type: | Book Chapter |
|---|---|
| Additional Information: | Doi: 10.1007/978-3-319-26555-1_15 |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences |
| Depositing User: | Rohitash Chandra |
| Date Deposited: | 10 Mar 2016 04:20 |
| Last Modified: | 06 Sep 2016 01:04 |
| URI: | https://repository.usp.ac.fj/id/eprint/8428 |
Actions (login required)
 |
View Item |