Improved Ant Colony Optimization with Particle Swarm Optimization Operator Solving Continuous Optimization Problems

Ant colony optimization (ACO) has the disadvantages such as easily relapsing into local optima and. Aimed at improving this problem existed in ACO, several new betterments are proposed and evaluated. In particular, pheromone mutation and particle swarm optimization operator were inducted. Then an improved ant colony optimization with particle swarm optimization operator was put forward. It was tested by a set of benchmark continuous function optimization problems. And the results of the examples show that it can not easily run into the local optimum and can converge at the global optimum.