MD-HACO is tested on widely used multi-objective multi-dimensional knapsack problem (MOMKP) instances and compared to well-known state-of-the-art algorithms. A multi-directional set holding the non-dominated solutions according to all directional archives is maintained. Afterward, a local search phase is applied to each sub-direction to enhance the search process toward the extreme Pareto-optimal solutions with respect to the weight vector under consideration. During the construction process, Ants optimize different search directions in the objective space trying to approximate small parts of the Pareto front. The developed MD-HACO algorithm optimizes the overall quality of Pareto set approximation using different configurations of the hybrid approach by means of different directional vectors. In this paper, we propose an Ant Colony Optimization (ACO) algorithm coupled with multi-objective local search procedure, and evolve into a multi-directional framework. Finding a good compromise between intensification and diversification mechanisms is very challenging task when solving multi-objective optimization problems (MOPs).
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |