A method for solving continuous optimization problem using ant colony algorithm

Basic artificial ant colony algorithm is good at solving the optimization of discrete problem. A method for solving optimization problem with continuous parameters using ant colony algorithm is proposed in this paper. In the method, the size of artificial ant colony is determined according to the constrained field of this problem and the amount of change in objective function is introduced as heuristic factor of the algorithm. The searching region is reduced, moved and modified according to the transition probability dynamically. Our experimental results in continuous optimization show that this method has much higher convergence speed and the disadvantage of classical ant colony algorithm of not being suitable for solving continuous optimization problems is overcome.