Immune Genetic Multi-objective Optimization Algorithms Based on Non-dominated Sorting

The paper represented An Immune Genetic Multi-objective Optimization Algorithms based on non-dominated sorting.Based on Immune Genetic Algorithm, the algorithm evaluated individuals fitting values in current population using Pareto sorting method,used concentration as selection criteria to keep population good diversity.This algorithm also used the immune clone operation to generate new population and implemented global searching process.Then a tournament selection between parent and genetic population was adopted to obtain optimal solutions.The simulation results showed that the algorithm was better than NSGA-II algorithm in convergence and distribution capabilities.