Improved Ant Colony Algorithm with Pheromone Mutation and its Applications in Flow-shop Problems

Ant Colony Algorithm (ACA) has the disadvantages such as easily relapsing into local optimization and stagnation. Aimed at improving this problem existed in ACA, several new betterments are proposed and evaluated. In particular, pheromone mutation and stochastic search strategy were inducted. Then an improved ant colony algorithm with pheromone mutation was put forward. It was tested by a set of benchmark Travelling Salesman Problems from the Travelling Salesman Problem Library. And the results of the examples show that it can not easily run into the local optimum and can converge at the global optimum. The improved algorithm was used to solve the Flow-shop problems. It performs better than the other algorithms such as Genetic Algorithm.