| Ant Colony Optimization Algorithm(ACO) is a new stimulated evolutionary algorithmattacking hard combinatorial optimization problems. It has showed a great deal of salientcharacter and performed great value in its application. Choosing the analysis of character ofAnt System(the basic algorithms of ant colony)as the research background,this paper focuseson the principle,the model,the behavior and its characteristics. This paper also compares antcolony algorithm with genetic algorithm and simulated annealing on optimizationperformance by simulation research. The results are promising. Ant colony algorithmoutperforms the other two algorithms on both convergence rate and the quality of solution.The author raises a model of ant colony algorithm on the continuous space(general function)optimization problems basing on the analysis of improved ones. Finally the results obtainedvia computer simulation show its validity.Although some successful applications have been presented,ant colony optimizationalgorithm also has many problems for solving and making further investigate. The paper alsopoints out the research direction of it. |
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