Constrained Optimization by epsilon Constrained Particle Swarm Optimizer with epsilon-level Control

In this study, e constrained particle swarm optimizer ePSO, which is the combination of the e constrained method and particle swarm optimization, is proposed to solve constrained optimization problems. The e constrained methods can convert algorithms for unconstrained problems to algorithms for constrained problems using the e level comparison, which compares the search points based on the constraint violation of them. In the e PSO, the agents who satisfy the constraints move to optimize the objective function and the agents who don’t satisfy the constraints move to satisfy the constraints. Also, the way of controlling e-level is given to solve problems with equality constraints. The effectiveness of the e PSO is shown by comparing the e PSO with GENOCOP5.0 on some nonlinear constrained problems with equality constraints.

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