An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

Effective constrained optimization algorithms have been proposed for engineering problems recently. It is common to consider constraint violation and optimization algorithm as two separate parts. In this study, a pbest selection mechanism is proposed to integrate the current mutation strategy in constrained optimization problems. Based on the improved pbest selection method, an adaptive differential evolution approach is proposed, which helps the population jump out of the infeasible region. If all the individuals are infeasible, the top 5% of infeasible individuals are selected. In addition, a modified truncated epsilon-level method is proposed to avoid trapping in infeasible regions. The proposed adaptive differential evolution approach with an improved epsilon constraint process mechanism (I epsilon JADE) is examined on CEC 2006 and CEC 2010 constrained benchmark function series. Besides, a standard IEEE-30 bus test system is studied on the efficiency of the I epsilon JADE. The numerical analysis verifies the I epsilon JADE algorithm is effective in comparison with other effective algorithms.