A Novel Cosine Swarm Algorithm for Solving Optimization Problems

In this paper, a robust swarm-inspired algorithm has been proposed known as Cosine algorithm (CA) to solve the optimisation problem. The CA generates several initial random agents' solution and requires all of them to change towards or outwards the ideal solution by means of mathematical model on Cosine function. A number of adaptive and random variables are also added into this method to promote exploitation and exploration of the search space at certain optimization milestones. The results of performance metrics and test functions demonstrate that the developed algorithm is capable of successfully exploring diverse areas of a search space, avoiding local optima, converging towards the worldwide optimum and exploiting potential parts of a search space through optimisation.