Affiliation:
1. Azarbaijan Shahid Madani University
2. Azarbaijan Shahid Madani University Faculty of Information Technology
Abstract
Abstract
The learning and teaching power of the students in different courses can be different according to their intelligence and talent. A student may be smart in one course while being lazy in other courses. In order to increase the efficiency of a class, regardless of the class teacher, it is better to teach each course by the smartest student in that course. Inspired by this fact, we present a new meta-heuristic optimization algorithm called Participation of Smart Students (PSS) in increasing the class efficiency. To analyze the effectiveness of the PSS algorithm, we run it on 10 general test functions and 29 test functions from the 2017 IEEE Congress on Evolutionary Computation (CEC 2017). The results of PSS algorithm are compared with the effectiveness of Teaching and Learning-based Optimization (TLBO) Algorithm, Black Widow Optimization (BWO), Political Optimization (PO), Barnacle Mating Optimizer (BMO), Chimpanzee Optimization Algorithm (CHOA), Aquila Optimizer (AO) and City Council Evolution (CCE). Multiple comparison of the results obtained by the Friedman rank test shows that the PSS algorithm has a higher efficiency than the TLBO, BWO, PO, BMO, CHOA, and AO algorithms and almost similar efficiency as the CCE algorithm in terms of finding the closest solution to the optimal one and the hit rate. Moreover, the PSS algorithm has a higher convergence speed than all other algorithms.
Publisher
Research Square Platform LLC
Reference58 articles.
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