Path Optimization Research Of Hybrid Based On Genetic Algorithms And Ant Colony Algorithms

Traveling salesman problem,as all people known, is a classic combinatorial optimization question,meanwhile ,it is a NP complete problem, in practice which is widely used, for example, including in printed circuit board manufacturing,extra-large scale integrated chip manufacturing, , robot research, robot control and other fields. Thus, researchers have been trying to find a solution of the existing high-quality, but also the best or fast convergence of the approximation algorithm ,For solving the traditional problem, such as: greedy algorithm method, local search method, branch and bound method, the multilateral exchange Adjustment Act, spanning tree doubling law. In recent years, there have been some kind bionic optimization algorithm, such as genetic algorithm, ant algorithm, simulated annealing, neural networks. Of these algorithms with a number of classical combinatorial optimization algorithm for the organic integration of a large extent, improved the convergence speed and improve understanding of quality.Genetic algorithm is a reference biosphere and evolutionary mechanisms of natural selection developed the probability of the global search algorithm. Among the many ways to solve the traveling salesman problem, genetic algorithm with other methods do not have a lot of advantages for small and medium-scale traveling salesman problem, genetic algorithm can get the optimal solution for large-scale traveling salesman problem, you can get approximate optimal solution.Ant algorithm as a class of heuristic algorithms have been successfully applied to solve the traveling salesman problem. Ants by secreting pheromone better path to strengthen the intensity of pheromone, while according to intensity of pheromone on the path to select the next choice of the path, a good path will be more and more ants choose, thereby allowing more pheromone will be covered by a good path, eventually all the ants are concentrated to a good path. This ant pheromone-based principles of positive feedback is the key to the whole algorithmBy the research of Genetic algorithm and ant pheromone-based principlesm,This article will explore the integration of genetic algorithms for solving problems in the TSP, the main study are as follows:(1) overview the research background of the traveling salesman problem, research status, purpose, meaning and major tasks of this article, an overview of the traveling salesman problem definition, mathematical model and classification of rough analysis of several classic Traveling Salesman Problem Algorithm(2), genetic algorithm and ant colony algorithm and its characteristics, the basic principles of research related to the status quo and its improved algorithm(3) the characteristics of hybrid genetic algorithm, basic principles, describes several ways to resolve the hybrid genetic algorithm for traveling salesman problem, and then proposes a new hybrid algorithm. And a detailed description of the algorithm design and coding scheme, Finally, the experimental results. Simulation results show that the new algorithm optimize the quality and efficiency are superior to the traditional ant colony algorithm and genetic algorithm.Finally, the full text studies were summarized, and prospects of genetic optimization algorithm should further study.