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.
Highlights
In many applications, such as in engineering, businesses and industrial designs, optimization is extremely important
Another reason is due to the so-called no free lunch (NFL) theorem, which reads that no universal algorithm exists for all problems [1]
The results showed that the modified camel algorithm is preferable when compared with particle swarm optimization (PSO) and the crow searching algorithm (CSA)
Summary
In many applications, such as in engineering, businesses and industrial designs, optimization is extremely important. [12] proposed a modern model for optimization that was inspired by nature called the squirrel search algorithm (SSA). This optimization algorithm imitates the southern flying squirrel’s complex foraging behavior and its effective method of transport known as gliding. Simulations annealing can almost guarantee that the ideal arrangement is found if the cooling process is moderate and the simulation is sufficiently long [15] In this study, another metaheuristic technique was proposed, known as the moss rose optimization algorithm (MROA), which is based on the flowering of this type of plant. A brief overview of the algorithm is given, and a comparison with other algorithms is provided to show that the proposed algorithm works correctly
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