Handling equality constraints by adaptive relaxing rule for swarm algorithms
Neural and Evolutionary Computing
2007-05-23 v1
Abstract
The adaptive constraints relaxing rule for swarm algorithms to handle with the problems with equality constraints is presented. The feasible space of such problems may be similiar to ridge function class, which is hard for applying swarm algorithms. To enter the solution space more easily, the relaxed quasi feasible space is introduced and shrinked adaptively. The experimental results on benchmark functions are compared with the performance of other algorithms, which show its efficiency.
Cite
@article{arxiv.cs/0505068,
title = {Handling equality constraints by adaptive relaxing rule for swarm algorithms},
author = {Xiao-Feng Xie and Wen-Jun Zhang and De-Chun Bi},
journal= {arXiv preprint arXiv:cs/0505068},
year = {2007}
}
Comments
Congress on Evolutionary Computation, 2004. CEC2004. Volume: 2, On page(s): 2012- 2016 Vol.2