A novel boundary constraint-handling technique for constrained numerical optimization problems

In this paper a new boundary constraint-handling technique called “centroid” is proposed to keep the search within the valid ranges of decision variables in a constrained numerical optimization problem. Such technique is based on computing the centroid of three solutions within the search space, one taken from the population and two generated at random. A comparison of the proposed technique in three experiments against other approaches found in the specialized literature is carried out by using a well-known scalable benchmark of 18 test problems. The results show that the proposed technique is able to promote better final results and improving both, the approach to the feasible region and the ability to generate better solutions.