Chimp Optimization Algorithm(ChOA)is one of the most efficient recent optimization algorithms,which proved its ability to deal with different problems in various ***,ChOA suffers from the weakness of the local search ...
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Chimp Optimization Algorithm(ChOA)is one of the most efficient recent optimization algorithms,which proved its ability to deal with different problems in various ***,ChOA suffers from the weakness of the local search technique which leads to a loss of diversity,getting stuck in a local minimum,and procuring premature *** response to these defects,this paper proposes an improved ChOA algorithm based on using Opposition-based learning(OBL)to enhance the choice of better solutions,written as ***,utilizing Reinforcement Learning(RL)to improve the local research technique of OChOA,called *** way effectively avoids the algorithm falling into local *** performance of the proposed RLOChOA algorithm is evaluated using the Friedman rank test on a set of cec 2015 and cec 2017 benchmark functions problems and a set of cec 2011 real-world *** results and statistical experiments show that RLOChOA provides better solution quality,convergence accuracy and stability compared with other state-of-the-art algorithms.
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