The Multi-objective Differential Evolution Algorithm Based on Quick Convex Hull Algorithms

The convex hull of a set of points is the smallest convex set that contains the points. This article presents a multi-objective differential evolutionary algorithm based on quick convex hull algorithms. In the improving multi-objective optimization algorithm, the Pareto-optimal solutions are selected by some new techniques. The non-dominated solutions are picked out from dominated solutions by the quick convex hulls algorithm. It can quickly locate the non-dominated solutions. The solutions provided by the proving algorithm for five standard test problems, is competitive to some known multi-objective optimization algorithms. Moreover, it obtains a well-converged and well-distributed set of Pareto optimal solutions in a small computational time.