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An Improved Ant Colony Algorithm for Continuous Domain and Its Convergence Analysis

LIU Wen

Abstract


In order to solve the main problems of continuous domain ant colony optimization algorithm, namely the problems of large complexity and large number of iterations, this paper proposed an improved ant colony algorithm of fine mining solution space; this algorithm can effectively achieve global quick search. The new algorithm’s specific steps were presented and its convergence was proved. Simulation experiments were carried out to compare in details among the improved ant colony algorithm, existing continuous domain ant colony algorithm and other intelligent optimization algorithms. Simulation results showed that: convergence speed, global search performance and optimal performance of improved ant colony algorithm were improved significantly. A theoretical basis was provided for improving the performance of continuous domain ant colony optimization algorithm.

Keywords


continuous domain, swarm intelligence, ant colony optimization algorithm, fine excavation, global optimization.

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