Abstract: Ant Colony Algorithm is a brand-new bionic simulated evolutionary algorithm, which has been applied to many fields. Multi-objective optimization problems are very important optimization problems. It's hard to optimized or solved. An improved Ant Colony Algorithm to solve Multi-objective optimization problems is introduced. After setting up a set of weight for the parameters, the algorithm uses some ants search in the solution space first in a stochastic way then stimulate the food searching behavior of real ants to guide the search by the pheromone. The new algorithm is explained in details and some simulations show the algorithm is very effective in finding global optimizations.