Mother Optimization Algorithm: A New Human-Based Metaheuristic Approach for Solving Engineering Optimization

Abstract

Abstract This paper presents a new metaheuristic method called Mother Optimization Algorithm (MOA) that mimics the human interaction between a mother and her children. The fundamental inspiration of MOA is to simulate the mother's care of children in three phases education, advice, and upbringing. The mathematical model of MOA used in the search process and exploration is presented. The performance of MOA is assessed on a set of 52 benchmark functions, including unimodal and high-dimensional multimodal functions, fixed-dimensional multimodal functions, and the CEC 2017 test suite. The results indicate that MOA's proposed approach, which balances exploration and exploitation, effectively supports the search process and can generate appropriate solutions for optimization problems. The outcomes quality obtained from MOA has been compared with the performance of twelve often-used metaheuristic algorithms. Upon analysis and comparison of the simulation results, it was found that the proposed MOA outperforms competing algorithms with superior and significantly more competitive performance. Specifically, the proposed MOA delivers better results in most objective functions. Furthermore, the application of MOA on four engineering design problems demonstrates the efficacy of the proposed approach in solving real-world optimization problems.