MTLBO: A Multi-objective Multi-course Teaching-Learning-based Optimization Algorithm

ABSTRACT This paper presents a multi-objective evolutionary algorithm, which is called multi-course teaching-learning-based optimization algorithm. It consists of four phases: teacher, leaner, teacher training, and exchange student phases. Three novel modifications are introduced into the basic teaching-learning-based optimization algorithm. It helps diversify evolutionary population, enhance stochastic search ability, and avoid premature convergence. Eight widely used benchmark problems are employed in order to investigate the performance of the proposed algorithm. The experimental results indicate that it finds better Pareto optimal solutions than some other state-of-the-art algorithms for the majority of problems.