مشخصات پژوهش

The learning and teaching power of the students in different courses can be different according to their intelligence and talent. One student can be smart in a single course while he/she is lazy in other courses. After teaching all courses by the class teacher, the lazy students in each course are taught again by the smart student in the course. Inspired by this fact, we present a new metaheuristic optimization algorithm called Participation of Smart Students (PSS) in increasing the class efficiency. The effectiveness of the PSS algorithm has been analyzed by 10 general test functions, 9 test functions from CEC 2019, and 12 test functions from CEC 2022. The results of PSS algorithm are compared with the effectiveness of eight recently developed well-known algorithms, i.e., Teaching and Learning-based Opti- mization (TLBO) Algorithm, Barnacle Mating Optimizer (BMO), Black Widow Optimization (BWO), Chimpanzee Optimization Algorithm (CHOA), Aquila Optimizer (AO), Reptile Search Algorithm (RSA), Prairie Dog Optimization (PDO), and Fick’s Law Optimization (FLA). Comparison of the results obtained by the Friedman rank and Wilcoxon signed-rank tests, for all 31 test functions, shows that PSS outperforms TLBO, BMO, BWO, CHOA, AO, RSA, PDO, and FLA algorithms by 38%, 38%, 64%, 74%, 45%, 64%, 58%, and 35%, respectively. Moreover, the PSS algorithm has a higher convergence speed and hit rate (= 35%) than all other compared algorithms. Finally, the reported results of solving two practical optimization problems by the PSS algorithm confirm its higher effectiveness compared to some good algorithms in the literature.