An immunity-based ant system for continuous space multi-modal function optimization

An immunity based ant system for solving continuous space multi-modal function optimization problems was proposed. By dividing the space into subdomains, in each iteration of the ant searching, the ants first find the subdomain in which the solution is located according to the pheromone trail, and then the precision values of the solutions are determined by immune operation. The algorithm was applied to multi-modal function optimization and compared with genetic algorithm (GA), the results show that it has higher performance than GA in global searching, and it presented a new method for ant system for solving continuous optimization problems.