An ocean water current-inspired Geoscience based optimization algorithm

A novel optimization technique is proposed based on ocean water currents. The combination of all-natural forces determines ocean current speed, further when resultant of all these forces nears to zero, stability is attained. Ocean water current optimization is the natural way to reach the stability point or the optimized point. The proposed evolutionary algorithm simulates the involved forces to generate Ocean Current Speed Index (OCSI), which further converges to the stability point. Compared to other nature-inspired algorithms, the proposed algorithm converges quickly due to an improved gradient descent algorithm. OWCO doesn’t get struck in local minima as the exploratory property of the algorithm uses highly mutating forces to generate new possible search spaces. Results with respect to CEC 2021 benchmark concludes that the proposed algorithm outperforms other contemporary algorithms in the context of application and empirical evaluations. This optimization algorithm is tested for D = 10 and D = 20 in CEC 2021 and found to be scalable with better exploration and convergence for single objective bound constraint problems.