A Novel Metaheuristic Moss-Rose-Inspired Algorithm with Engineering Applications

Abstract

Every day, a moss rose generates new flowers with variable diameters. Two flowering mechanisms are controlled by exposure to sunlight, namely, a variable concentration of florigen based on photoreceptors called phytochromes, and the biological clock, which is responsible for the changing diameters of the plant flowers at night and some hours during the day. By explaining and idealizing the flowering mechanisms of the moss rose in nature, a new sort of nature-inspired optimization algorithm called the moss rose optimization algorithm (MROA) was proposed in this study. The MROA was benchmarked using three methods. First, 18 benchmark functions were utilized to evaluate the effectiveness of the MROA. Second, the MROA was used for planning a smart antenna system (SA) as an online solution to find unknown weights. Third, the MROA was used to find the optimal dimensions for a microstrip antenna for the frequency (2.4 GHz) as an offline solution. The MROA was compared with other algorithms. The results show the capacities and proficiencies of the proposed algorithm regarding finding the ideal solutions. The promising arrangements for smart antenna identification and microstrip antenna design highlight the importance of this algorithm for resolving current issues with unknown fields of investigation.