抄録
In some optimization problems where user's preference should be considered, it is difficult to build the preference into the evaluation function quantitatively. We adopt the following approach for solving the issue: An intelligent system presents two or more candidate solutions which have good evaluation values in the viewpoints except for user's preference, and the user chooses a favorite one out of the set of the solutions. In this research, to construct such a system for the combinatorial optimization problems, we aim to propose Ant Colony Optimization (ACO) method which can search two or more high-quality diverse solutions. ACO is one of the methods to solve the Traveling Salesman Problems (TSPs). This method basically outputs only one discovered best solution by a single run. In this paper, we introduce tabu search mechanism into ACO for discovering diverse solutions in a single colony. Ants register the discovered solutions in a tabu list as ants search for the optimal solution. When the best found solution is not updated for a certain period, the search is regarded as converged. Then, ants search different solutions from ones registered in the tabu list. We applied the proposed methods to some TSPs, and confirmed that the acquired diverse solutions are useful for users' decision makings.
