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novel evolutionary algorithm called learner performance based behavior
algorithm (LPB) is proposed in this article. The basic inspiration of LPB
originates from the process of accepting graduated learners from high school in
different departments at university. In addition, the changes those learners
should do in their studying behaviors to improve their study level at
university. The most important stages of
optimization; exploitation and exploration are outlined by designing the
process of accepting graduated learners from high school to university and the
procedure of improving the learner’s studying behavior at university to improve
the level of their study. To show the accuracy of the proposed algorithm, it is
evaluated against a number of test functions, such as traditional benchmark
functions, CEC-C06 2019 test functions, and a real-world case study problem. The
results of the proposed algorithm are then compared to the DA, GA, and PSO. The
proposed algorithm produced superior results in most of the cases and
comparative in some others. It is proved that the algorithm has a great ability
to deal with the large optimization problems comparing to the DA, GA, and PSO.
The overall results proved the ability of LPB in improving the initial
population and converging towards the global optima. Moreover, the results of
the proposed work are proved statistically.