NiOA: A Novel Metaheuristic Algorithm Modeled on the Stealth and Precision of Japanese Ninjas

Abstract

This paper presents a new metaheuristic optimization algorithm called the Ninja Optimization Algorithm (NiOA) owing to its characteristics such as stealth, precision, and adaptability of the ninjas of Japan. NiOA is proposed to avoid high exploration and exploitation costs within such complex search spaces and to avoid the problem of getting trapped in local optima. The algorithm imitates ninja searching techniques because it has a scanning phase, adapted to search large areas to look for answers, while the more specific phase is used to refine the answers found. The performance of NiOA is compared with other benchmark optimization functions and some of the frequently used CEC 2005 benchmarks. These benchmarks are well suited to test unimodal and multimodal optimization problems of good quality. Experimental results prove that NiOA can significantly provide better optimization results regarding solution quality, convergence rate, and time complexity, suggesting that NiOA is a robust algorithm for solving high-dimensional large-scale optimization problems. Furthermore, it reveals that NiOA is applicable to solve different kinds of problem spaces, signifying that NiOA can be used in practice on scientific and engineering problems.