Opposition Based Salp Swarm Algorithm for Numerical Optimization

Abstract

In this paper an improved optimization algorithm called Opposition Based Salp Swarm Algorithm (OSSA) is proposed. This is improved version of recently proposed Salp Swarm Algorithm (SSA), which mimics swarming acts of salps when foraging and navigating in oceans. To improve the performance of SSA, Opposition based learning (OBL) is introduced in Salp Swarm Algorithm. The algorithm is evaluated on several numerical standard functions and is compared with some well known optimization algorithms.