Constraint-handling techniques within differential evolution for solving process engineering problems

Abstract

A wide range of process systems engineering problems involve an optimisation formulation that is difficult to solve due to sources of discontinuity and non-convexity and a high number of constraints to satisfy. Differential Evolution algorithm (DE) has proven to be robust for the solution of highly non-convex and mixed-integer problems; nevertheless, its performance greatly depends on the constraint-handling technique used. In this study, numerical comparisons of some state-of-the-art constraint-handling techniques are performed: static penalty function, stochastic ranking, feasibility rules, ε constrained method and gradient-based repair. The obtained results show that the gradient-based repair technique deserves a special attention when solving highly constrained problems. This technique enables to efficiently satisfy both inequality and equality constraints, which makes it particularly adapted for the solution of process engineering optimization problems.