Efficient constraint handling scheme for differential evolutionary algorithm in solving chemical engineering optimization problem

This paper introduces a new constraint handling scheme developed for the differential evolutionary algorithm to solve constrained optimization problems. The developed approach uses a repair algorithm based on the gradient information derived from the equality constraint set to correct infeasible solutions. A dominance-based selection scheme is also applied to incorporate constraints into the objective function. To illustrate the developed algorithm and to compare its efficiency with other tradition method, several test problems and chemical engineering optimization problems are used. A traditional constraint handling technique is compared; both in terms of solution quality and the number of function evaluations required. The performance of our developed scheme compares favorably with traditional penalty function method. Our developed algorithm can effectively handle constraints encountered in chemical engineering optimization problems.