Abstract
Bonobo optimizer (BO) is a novel metaheuristic algorithm motivated bythe social behaviour of the bonobos. This paper presents a quantum behaved bonobo optimization algorithm (QBOA) employing an innovative metaheuristic based on the reproductive strategies and social behavior of bonobos.Whereby, the quantum mechanics are embedded into the bonobo optimizerto direct the search agents through the search space. Accordingly, under thisquantum-behaved movement, the proposed QBOA’s exploitation capability ispromoted. The performance of the proposed QBOA is exhibited on CEC2005and CEC2019 benchmarks. Moreover, the QBOA algorithm was adapted tooptimize the dynamic photovoltaic models parameters. QBOA exhibits theefficiency and adequacy to solve various optimization problems based on experimental and comparison findings, as well as its ability to implement competitiveand promising results optimizing dynamic photovoltaic models
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