Abstract: This study presented a dynamic self-adaptive harmony search (DSHS) algorithm to solve high-dimensional optimization problems. In the proposed DSHS algorithm, the orthogonal experimental design algorithm was used to initialize population;two new harmony adjustment operators,multi-dimensional dynamic adaptive adjustment operator and oncdimensional tones finctuning operator, were integrated to the improvisation scheme. For avoiding the search being trapped in local optimum,an improved band width adjustment algorithm was employed to enhance the disturbance performance. 6 benchmark function experiments show that the proposed algorithm has strong convergence velocity, stabilination and capacity of space exploration on solving high-dimensional complex optimization problems, compared with most other approaches.

Key words: High-dimensional, Dynamic self-adaptive, Harmony search algorithm