Sandpiper optimization algorithm: a novel approach for solving real-life engineering problems

摘要

This paper presents a novel bio-inspired algorithm called Sandpiper Optimization Algorithm (SOA) and applies it to solve challenging real-life problems. The main inspiration behind this algorithm is the migration and attacking behaviour of sandpipers. These two steps are modeled and implemented computationally to emphasize intensification and diversification in the search space. The comparison of proposed SOA algorithm is performed with nine competing optimization algorithms over 44 benchmark functions. The analysis of computational complexity and convergence behaviors of the proposed algorithm have been evaluated. Further, SOA algorithm is hybridized with decision tree machine-learning algorithm to solve real-life applications. The experimental results demonstrated that the proposed algorithm is able to solve challenging constrained optimization problems and outperforms the other state-of-the-art optimization algorithms.