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In order to overcome the convergence deficiency of the basic ACO, an improved ACO based on the direction of the logistics and distribution problem was proposed. The logistics optimization method was used to optimize the path finding in the ACO. The simulation results show that the method of optimization of logistics and distribution path is practical and effective. This study provides a new powerful...
Ant Colony Optimization (ACO) algorithms belong to class of Meta-heuristic algorithms, where a search is made for optimized solution rather than exact solution, based on the knowledge of the problem domain. ACO algorithms are iterative in nature. As the iteration proceeds, solution converges to the optimized solution. In this paper, we examine the pheromone trial, a knowledge repository for ants,...
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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