Electricity generation using photovoltaic (PV) technology has become highly popular recently. However, natural barriers such as trees, buildings, bird drops, etc., cause partial shading (PS) on the PV surface resulting in high power losses. Bypass diodes used to mitigate the PS effect cause multiple peaks in the PV power delivery. The tracking of the optimal power peak can be considered an optimization problem with a continuously changing objective function due to different insolation conditions. All optimization strategies applied in previous works spanning from mathematical programming techniques to Machine Learning and the recently proposed Nature-inspired algorithms led to either sub-optimal maximum power or required extensive computations. This work presents an algorithm that combines the advantages of the previous works and avoids their loopholes. Experimental results indicate the superiority of the proposed algorithm over the state-of-the-art algorithm for the Maximum Power Peak Tracking problem.