Xerus Optimization Algorithm (XOA): a novel nature-inspired metaheuristic algorithm for solving global optimization problems

Document Type: Research Paper

Authors

1 Faculty of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran.

2 University of Tehran, College of Engineering, Faculty of Engineering Science

Abstract

Over the recent years, many research has been carried out on applying the optimization approach to science and engineering problems. Thereby, numerous metaheuristic algorithms have been developed for solving such type of challenge. Despite an increase in the number of these algorithms, there is currently no specific algorithm which can be employed to optimize all varieties of problems. In the current research, a novel metaheuristic algorithm for global and continuous nonlinear optimization, named as Xerus Optimization Algorithm (XOA) has been introduced. XOA has been inspired by group living and lifestyle of cape ground squirrels (Xerus inauris), by taking into account their co-operation in living together, hunting, and communication, etc. In order to evaluate the efficiency of XOA, algorithms for 30 different benchmarks have been analyzed and compared to some novel and renowned metaheuristic algorithms. The simulation response illustrates a significant improvement in  the performance of the novel XOA, in comparison to the algorithms presented in the literature. The proposed algorithm can be employed for many applications that require a solution to different optimization problems.

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