Multi-Agent Tabu Search based on Proximate Optimality Principle

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  • 近接最適性の原理に基づく多点探索型Tabu Search
  • キンセツ サイテキセイ ノ ゲンリ ニ モトズク タテン タンサクガタ Tabu Search

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Abstract

This paper presents a new method for solving large-scale combinatorial optimization problems. The proposed method named Multi-agent Tabu Search is based on Tabu Search and takes the concept of Proximate Optimality Principle (POP) into consideration. Tabu Search is one of the most powerful methods for solving combinatorial optimization problems. In order to achieve well-balanced search for solving combinatorial optimization problems, the proposed method coordinates two different purposes - the value of an objective function and the evaluation of POP in search process. While the feasibility and advantages of the autonomous and proposed adaptive PSO algorithm are demonstrated through numerical simulations using typical combinatorial optimization problems, more detailed numerical examination is needed to confirm whether the proposed method has better performance on search ability than the conventional Tabu Search or not.

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