Proximate Optimality Principle Based Tabu Search

Abstract

Meta-heuristics is a new paradigm that aims to obtain an approximate solution within a feasible computation time. In the meta-heuristics, Tabu Search is one of the most effective algorithms for solving combinatorial optimization problems. While the intensification of Tabu Search is powerful, the diversification of Tabu Search is not powerful. This paper proposes an algorithm - Multi Criteria Tabu Search coordinating the intensification and the diversification based on a Proximate Optimality Principle (POP) - which has several advantages for solving combinatorial optimization problems. The proposed algorithm is applied to some traveling salesman problems which are typical combinatorial optimization problems in order to verify the performance of the proposed algorithm. © 2004, The Institute of Electrical Engineers of Japan. All rights reserved.