Using Manta Ray Foraging Mechanism to Improve Reptile Search Algorithm

The reptile search algorithm (RSA) is a novel, nature-inspired meta-heuristic algorithm. This algorithm mainly simulates the predatory behavior of crocodiles to achieve optimal solutions. It possesses rapid convergence speed along with robust optimization capabilities. However, due to its excessively fast convergence speed, RSA can easily fall into local optimality. This paper first proposes a hybrid algorithm called MRFORSA by adding the manta ray foraging optimization (MRFO) mechanism to help RSA better jump out of the local optimum. Experimental findings using the IEEE CEC2017 benchmark function indicate that MRFORSA exhibits strengths in terms of solution quality and convergence velocity.