Multi-swarm UPSO algorithm based on seed strategy for atomic clusters structure optimization |
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| Affiliation: | 1. Department of Organic Chemistry, Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 19, 10 000 Zagreb, Croatia;2. Department of General and Inorganic Chemistry, Institute of Chemistry, Faculty of Engineering, University of Pannonia, P.O.B. 158, Veszprém H-8201, Hungary;3. NMR Center, Rudjer Bošković Institute, Bijenička cesta 54, 10 000 Zagreb, Croatia;1. College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, People''s Republic of China;2. College of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210046, People''s Republic of China;3. Key Laboratory of Radio Frequency and Micro-Nano Electronics of Jiangsu Province, Nanjing 210023, Jiangsu, People''s Republic of China;4. Department of Mathematics and Physics, Nanjing Institute of Technology, Nanjing 211167, Jiangsu, People''s Republic of China;1. Department of Chemistry, Indian Institute of Technology Roorkee, Roorkee 247 667, India;2. Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee 247 667, India;1. Materials Science Laboratory, School of Physics, Vigyan Bhawan, Devi Ahilya University, Khandwa Road Campus, Indore 452001, India;2. School of Physics, Indian Institute of Science Education and Research, Thiruvananthapuram 695016, India;1. Department of Applied Physics, Guru Jambheshwar University of Science & Technology, Hisar 125001, Haryana, India;2. National Physical Laboratory, Dr. K. S. Krishnan Marg, New Delhi 110012, India |
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| Abstract: | 
Particle Swarm Optimization (PSO) algorithm is prone to get trapped in local optima and insufficient information exchange among particles. To solve this problem, this paper proposes a Multi-swarm Unified Particle Swarm Optimization algorithm based on Seed Strategy (SS-DMS-UPSO) to optimize the atomic clusters structure. In this algorithm, the population is divided into some sub-populations evolving randomly and evenly, and each sub-population uses UPSO algorithm with different unification factors to evolve independently in parallel. After a certain number of independent evolution, the particles of all sub-populations are merged into a new population, and the population is again randomly divided into average sub-populations. Iterate the algorithm repeatedly in this way. And finally the global best particle can be obtained. The experimental results show that the SS-DMS-UPSO algorithm can search for the optimal structure or extremely similar optimal structure for atomic clusters with atomic numbers between 2 and 31. For atomic clusters with atomic numbers between 32 and 35, the algorithm can find its approximate optimal structure. Compared with other algorithms, the difference between the lowest energy value and the ideal energy value obtained by the SS-DMS-UPSO algorithm is much smaller. It means that its optimal structure of the atomic clusters is closer to the stable structure, and the algorithm is more stable, which proves the effectiveness of the SS-DMS-UPSO algorithm. |
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| Keywords: | Atomic clusters Multi-swarm mechanism Particle swarm optimization Seed strategy Unified particle swarm optimization Information communication strategy |
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