  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.
