Hybrid Taguchi-Immune Algorithm for the thermal unit commitment

In this paper, a Hybrid Taguchi-Immune Algorithm (HTIA) is presented to deal with the unit commitment problem. HTIA integrates the Taguchi method and the Traditional Immune Algorithm (TIA), providing a powerful global exploration capability. The Taguchi method (TM) is incorporated in the crossover operations in order to select the better gene for achieving crossover consequently, enhancing the TIA. It has been widely used in experimental designs for problems with multiple parameters. The effectiveness and efficiency of HTIA are demonstrated by presenting several cases, and the results are compared with previous publications. Our results show that the proposed method is feasible, robust, and more effective than many other previously developed computation algorithms.

Research highlights
► We develops a Hybrid Taguchi-Immune Algorithm (HTIA) is presented to deal with the unit commitment problem.
► HTIA integrates the Taguchi method and the Traditional Immune Algorithm (TIA).
► The systematic reasoning ability of TM is integrated in the crossover operations to select better chromosomes for representing the new potential offspring and dealing with the local optimality problem.
► TIA can use in experimental designs for problems with multiple parameters.