An efficient hybrid Taguchi-immune algorithm for the unit commitment problem

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. Taguchi method (TM) has been widely used in experimental designs for problems with multiple parameters, and is incorporated into TIA in this paper for the crossover operation to select a better gene. The effectiveness and efficiency of HTIA are demonstrated by several case studies, and the results are compared with other methods published before. Test results show that the proposed method is feasible, robust, and more effective than many other previously developed computation algorithms.

► HTIA integrates the Taguchi method and the Traditional Immune Algorithm.
► HTIA provides a powerful global exploration capability.
► HTIA is presented to deal with the unit commitment problem.
► TM was incorporated in the crossover operations to select a better gene.