Abstract: By integrating the advantages of both genetic algorithm and ant colony algorithm,this paper presents a multi-population genetic algorithm with ant search.In this algorithm,populations evolve independently,and worse chromosomes of each population are replaced by solutions obtained from ant search,so as to increase the diversity and improve the quality of populations.By setting the initial pheromone trail based on the best chromosomes of each population,the accumulation process of pheromone trail is greatly shortened,and the searching speed of ants is quickened.This algorithm has been used to solve a benchmark job shop scheduling problem.Simulation result shows that the algorithm is effective.