An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems

Teachinglearning-based optimization (tlbo) algorithms simulate the teachinglearningphenomenon of a classroom to solve multi-dimensional, linear and nonlinear problems with appreciableefficiency. in this paper, the basic tlbo algorithm is improved to enhance its exploration and exploitationcapacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial trainingand self motivated learning. performance of the improved tlbo algorithm is assessed by implementing iton a range of standard unconstrained benchmark functions having different characteristics. the results ofoptimization obtained using the improved tlbo algorithm are validated by comparing them with thoseobtained using the basic tlbo and other optimization algorithms available in the literature.