It means that a smaller iner1a weight can be adopted

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Unformatted text preview: (nt − t) + w (0) nt v i ( t ) = ω × v i (t − 1) + φ1 × ( pbest ( t − 1) − x i (t − 1)) + φ2 × ( gbest (t − 1) − x i ( t − 1)) € φ1 = b1 × r1 + d1, b1 = 1.5, d1 = 0.5 φ 2 = b2 × r2 + d2 , b2 = 1.5, d2 = 0.5 € 0.5 ≤ φ1, φ 2 ≤ 2 € € € 2 2/25/14 Ra1onal Discrete PSO for TSP •  PSO with a large iner1a weight has more possibility to converge [9], which implicates a larger iner1a weight in the end of a search will foster the convergence ability. •  However, a small iner1a weight is not always harmful, it makes PSO to jump out from local minima and explore new search areas. It means that a smaller iner1a weight can be adopted at the beginning of each search. •  K.P. Wang, L. Huang, C.G. Zhou, W. Pang, Par1cle swarm op1miza1on for traveling salesman problem, Interna1onal...
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