The epsilon constrained method is an algorithm transformation method, which can convert algorithms for unconstrained problems to algorithms for constrained problems using the epsilon level comparison that compares search points based on the constraint violation of them.
We proposed the epsilon constrained particle swarm optimizer epsilonPSO, which is the combination of the epsilon constrained method and particle swarm optimization.
The ePSO can run very fast and find very high quality solutions, but the ePSO is not very stable and sometimes can only find lower quality solutions.
On the contrary, the epsilonGA, which is the combination of the epsilon constrained method and GA, is very stable and can find high quality solutions, but it is difficult for the eGA to find higher quality solutions than the epsilonPSO.
In this study, we propose the hybrid algorithm of the ePSO and the eGA to find very high quality solutions stably.
The effectiveness of the hybrid algorithm is shown by comparing it with various methods on well known nonlinear constrained problems.