Improvement Of Ant Colony Optimization And Its Application In TSP

An amazing behavior of self-organization will usually be produced from the collective behavior of social animals. Take a colony of ants for example, blind ants can find the shortest routing path from their nest to food source. Inspired from this, a population-based simulated evolutionary algorithm called ant colony optimization (ACO for short) was proposed by Italian researchers M. Dorigo. Many scholars are attracted to study ACO and in the past ten years, the algorithm has been widely applied to the fields of combinatorial optimization, network routing, functional optimization, data mining, and path planning of robot etc, and good effects of application are gained.Centering on ACO's perfection and its application in TSP, this dissertation carries out an in-depth research on ways to improve the basic ACO algorithm, inhibit standstill of the algorithm, and well as the application of ACO in TSP. The main contributions of this dissertation are as follows: (1) Ant colony algorithm with path choice of dynamic transition. path choice rule is introduced, which based on contrast intensification technology, in order to increase the probability of selecting solution components, and path choice rule strengthen the use of feedback and speed up convergence speed. Information entropy is used to dynamic control to direction of contrast enhancement, which avoids stagnation of the algorithm and speed up convergence. (2) Combining the advantages of Immune algorithm and ant colony algorithm, Ant Colony Algorithm with Immune Mutation is put forward. In order to speed up the convergence speed, the algorithm makes use of contrast enhancement technology in the search process of solution of the probability, through introducing selection operators by amalgamating monoclonal and then initiates immunity strategies based on priori knowledge .The simulation results show that the improved algorithm performances favorable stability and global optimization,and it can avoid stagnation phenomenon in effective and accelerate the convergence speed.Finally, the work of this dissertation is summarized and the prospective of future research is discussed.