A novel binary differential evolution algorithm based on artificial immune system

Differential evolution, a heuristic optimization algorithm, has been successful in solving a wide range of real-value optimization problems. However, it is of low efficiency in dealing with the discrete problems. Tn this paper, a new binary differential evolution algorithm based on the theory of immunity in biology is proposed. In spite of the simplicity of the technique, simulation results show the improvement of the searching ability and increment in the convergence speed in comparison with the other binary particle swarm optimization.