Partheno Genetic Ant Colony Optimization Algorithm and its Application

Abstract

Ant colony algorithm is a kind of effective combinatorial optimization problem solving algorithm has been increasingly, thorough research, and gradually get used. Ant colony algorithm is a set of parameters, the algorithm, a lack of adequate experiences often. The paper has put forward a single genetic character of ant colony algorithm. Will the ant colony algorithm each search results as the initial population, single genetic improvement, for the shortest route optimization. In the traveling salesman problem of the experiments prove the effectiveness of the proposed algorithm.

Research on flight path planning method based on genetic ant colony algorithm and Maklink diagram

“…However, both algorithms have their own shortcomings. The ant colony algorithm has the disadvantages of a large amount of computation, a slow search process, and easy stagnation [5]. The improvement points of the genetic algorithm are mainly that it relies too much on the initial population, the population diversity is difficult to maintain, and the convergence speed is difficult to control [6].…”