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To avoid premature convergence and stagnation problems in classical ant colony system, a novel multi-behavior based multi-colony ant algorithm (MBMCAA) is proposed. The ant colony is divided into several sub-colonies; the sub-colonies have their own population evolved independently and in parallel according to four different behavior options, and update their local pheromone and global pheromone level...
An improved ant colony optimization algorithm is proposed in this paper. Comparing with the conventional ant colony optimization algorithm, the proposed method has two highlights. First, a newly strategy based on the dynamic control of solution construction is adopted. The purpose of this strategy is to ensure ants to exploit the solutions at the beginning of searching procedure with large probability...
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