Tabu Search を組み合わせた Particle Swarm Optimization の検討 [in Japanese] Consideration of Particle Swarm Optimization Combined with Tabu Search [in Japanese]
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This paper presents a new Particle Swarm Optimization based on the concept of Tabu Search. In PSO, when a particle finds a local optimal solution, all of the particles gather around the one, and cannot escape from it. On the other hand, TS can escape from the local optimal solution by moving away from the best solution at the present. The proposed Tabu List PSO (TL-PSO) is the method for combining the excellence of both PSO and TS. In this method, it stores the history of <i>pbest</i> in Tabu List. When a particle has a reduced searching ability, it selects a <i>pbest</i> of the past from the history of them, and it is applied to update. This makes each particle active, and the searching ability of swarm makes progress. Then, the proposed method is validated through numerical simulations with several functions which are well known as optimization benchmark problems comparing to the conventional PSO methods.
- IEEJ Transactions on Electronics, Information and Systems
IEEJ Transactions on Electronics, Information and Systems 128(7), 1162-1167, 2008-07-01
The Institute of Electrical Engineers of Japan