| Title | Research of Improved Ant Colony Algorithm and Its Application |
| Abstract | Ant colony optimization algorithm is a novel bionic evolutionary algorithm for complex combinatorial optimization problems. It has such characteristics as positive feedback, parallel computing, robustness and etc. However, it may be improved in many respects due to its complicity and immature .Therefore, its improvement is valuable for theoretical research practical application.Usually, the basic ant colony algorithm in solving combinatorial optimization problems can easily arise in the process of premature convergence or stagnation. In order to solve these problems, a new improved algorithm based on the basic ant colony algorithm is proposed in this paper and used in the path management of the vending machine.The main contents are composed of the following parts:1.The dissertation systematically summarizes the principles , theory and applications of ACO(Ant Colony Optimization) in TSP(Traveling Salesman Problem). A specific description of the basic model of ant colony algorithm, characteristics, composition and realization method are presented. The reasonable selection about the parameters is discussed in simulation tests. And the basic principles for parameters selected are also given.2. A new adaptive ant algorithm is proposed to overcome shortage of the traditional ant algorithm which easily appears precocious and stagnation behavior The improved one can dynamically adjust the parameter of pheromone of ant colony algorithm. some of simulations on typical TSP problems to experiment, illustrates that the new adaptive ant colony algorithm has a better ability to search the global optimal solution and have better stability and astringency.3. This job studies the route selecting of goods distribution in vending machines with ant colony algorithm. The particularity of the vending machine route selecting being different from the typical TSP problems is analyzed.The simulation tests of the improved ant colony algorithm through Matlab tools, shows that the presented algorithm has significant improvement in obtaining the optimal path and reducing the number of iterations, comparing to the basic ant colony algorithm. The result of this paper has some reference value for the research on the ant colony algorithm and application value for the path management of the vending machine. |
| Category | Internet |
| Keywords | ACS, pheromone, self-adaptive, TSP, |
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| Pages | 146 |
| Price | US$70.00 |
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Research of Improved Ant Colony Algorithm and Its Application
Billy HU, Ph.D
E-Mail:itpaper@hotmail.com
TEL:1-888-786-998A
