Adaptive differential evolution algorithm for nonlinear constrained optimization problems
Huirong Li · Computer Engineering and Applications Journal · 2011
This paper presents an improved adaptive differential evolution algorithm for the nonlinear constrained optimization problems.In this algorithm,the fixed weighting factor and crossover probability factor of the differential evolution are improved.The constrained optimization problems are converted into unconstrained bi-objective optimization problem by the definition of the constraint violation function.In each iteration,keeping a part of the performance of better infeasible particles is to maintain the diversity of the swarm.Mutation operator is introduced to expand the search range of the particle.Numerical experiments show that the proposed algorithm has faster convergence speed and better ability of global optimization.