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We present a particle swarm optimization algorithm OT-PSO using orthogonal test technique. Based on the classical PSO, OT-PSO searches for local optimum in the neighbor area of the global best solution by using the method of orthogonal test design. OT-PSO can probe the solutions uniformly distributed in the search space and select the better ones. Using those better solutions OT-PSO can guide the...
An adaptive parallel ant colony algorithm (PACO) is presented. In the algorithm, we propose a strategy for information exchange between processors which make each processor choose its partner to communicate and update the pheromone adaptively. We also propose a method of adjusting the time interval of information exchange adaptively according to the diversity of the solutions so as to increase the...
This paper presents a parallel-refined simulated annealing (PRSA) approach for the generator maintenance scheduling (GMS) problem to maximize profit objective function. The merit of simulated annealing (SA) is preserved and the deficiency is pruned away in the proposed PRSA. The proposed PRSA is an effective method because the multiple search trajectories parallel and refined in each stage. The near...
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