Abstract
In the real life learning process, the teacher communicates with the students for a better learning outcome. The teaching-learning-based optimization (TLBO) algorithm simulates this procedure and shows its great performance in solving the constrained and unconstrained nonlinear optimization problem. This paper presents an adaptive direction strategy（ADS ）t o improve the searching ability for the TLBO algorithm. The improved algorithm is tested through searching the optimal points for a few typical testing functions. The testing result shows that the improved TLBO algorithm could obtain better optimal solutions in shorter time. Compared to the normal TLBO algorithm, the stability and effectiveness of the improved algorithm are increased greatly.
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