An novel immune genetic algorithm and its application in WWTP

This paper proposes a novel immune genetic algorithm to increase the performances in the complex optimization problems. Rough search and local normal search are applied to immune genetic algorithm to improve convergence speed and solution accuracy separately. Numerical simulations are arranged among the proposed strategies, other three immune algorithms and some state-of-art-algorithms. The simulation results indicate that the proposed strategy outperforms the other algorithms in convergence speed and solution quality. It is also applied into a practical application of wastewater treatment process (WWTP) and can reduce the energy consumption effectively.