An Improved Adaptive Differential Evolution Approach for Constrained Optimization Problems

As the complexity of the real-world engineering problems increases, numerous efficient constraint-handling methods and optimization algorithms have emerged recently. However, the majority of the research consider the constraint-handling method and the optimization algorithm independently. In this paper, we propose a constraint-based mutation operator, in which the constraint violation and objective function are considered simultaneously. We define the pbest individuals as the best in top 5% constraint violators if all the individuals are infeasible. In this way, we could guide the population move towards the feasible region. Two real-world engineering applications are used to test the performance of the I epsilon JADE. Compared with the state-of-the-art algorithms, the experimental results illustrate the effectiveness of the I epsilon JADE algorithm, which also exhibits a fast convergence rate in terms of computation efficiency.