Effective search technique in teaching and learning phase of TLBO algorithm for numerical function optimisation

Optimisation is a very important process and plays a very vital role in many engineering and scientific researches. All optimisation algorithms have different search tendency to find the optimum value in the design space. However, the capability of the metaheuristic can be enhanced by modifying it with other efficient search techniques to make it more efficient and computationally effective. This paper explores the modifications in the basic teaching-learning-based optimisation (TLBO) algorithm with different effective search technique inspired from artificial bee colony (ABC) and particle swarm optimisation (PSO) algorithms for further enhancing the search capability of TLBO. To check the effectiveness of the proposed algorithm, 55 different benchmark problems from CEC2005 and CEC2014 were used. The proposed algorithm is also compared with other well-known metaheuristic methods. Statistical analysis is performed by Friedman rank test. The numerical comparison shows that the proposed algorithms are an alt...