Ant Colony Optimization Algorithm Model Based on the Continuous Space

Ant colony algorithm is a heuristic algorithm which is fit for solving complicated combination optimization. It showed great advantage on solving combinatorial optimization problem since it was proposed. The algorithm uses distributed parallel computing and positive feedback mechanism, and is easy to combine with other algorithms. This ant colony algorithm has already been widespread used in the field of discrete space optimization, however, is has been rarely used for continuous space optimization question. On the basis of basic ant colony algorithm principles and mathematical model, this paper proposes an ant colony algorithm for solving continuous space optimization question. Comparing with the ant colony algorithm, the new algorithm improves the algorithm in aspects of ant colony initialization, information density function, distribution algorithms, direction of ant colony motion, and so on. The new algorithm uses multiple optimization strategy, such as polynomial time reduction and branching factor, and improves the ant colony algorithm effectively.