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Dowlatshahi, M. B., Derhami, V., Nezamabadi-pour, H.. (1399). Fuzzy particle swarm optimization with nearest-better neighborhood for multimodal optimization. نشریه علمی دانشگاه سیستان و بلوچستان, 17(4), 7-24. doi: 10.22111/ijfs.2020.5403
M. B. Dowlatshahi; V. Derhami; H. Nezamabadi-pour. "Fuzzy particle swarm optimization with nearest-better neighborhood for multimodal optimization". نشریه علمی دانشگاه سیستان و بلوچستان, 17, 4, 1399, 7-24. doi: 10.22111/ijfs.2020.5403
Dowlatshahi, M. B., Derhami, V., Nezamabadi-pour, H.. (1399). 'Fuzzy particle swarm optimization with nearest-better neighborhood for multimodal optimization', نشریه علمی دانشگاه سیستان و بلوچستان, 17(4), pp. 7-24. doi: 10.22111/ijfs.2020.5403
Dowlatshahi, M. B., Derhami, V., Nezamabadi-pour, H.. Fuzzy particle swarm optimization with nearest-better neighborhood for multimodal optimization. نشریه علمی دانشگاه سیستان و بلوچستان, 1399; 17(4): 7-24. doi: 10.22111/ijfs.2020.5403

Fuzzy particle swarm optimization with nearest-better neighborhood for multimodal optimization

Iranian Journal of Fuzzy Systems
دوره 17، شماره 4، مهر و آبان 2020، صفحه 7-24    اصل مقاله (517.04 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22111/ijfs.2020.5403
نویسندگان
M. B. Dowlatshahi* 1؛ V. Derhami2؛ H. Nezamabadi-pour3
1Department of Computer Engineering, Faculty of Engineering, Lorestan University, Khoramabad, Iran.
2Department of Computer Engineering, Faculty of Engineering, Yazd University, Yazd, Iran.
3Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
چکیده
In the last decades, many efforts have been made to solve multimodal optimization problems using Particle Swarm Optimization (PSO). To produce good results, these PSO algorithms need to specify some niching parameters to define the local neighborhood. In this paper, our motivation is to propose the novel neighborhood structures that remove undesirable niching parameters without sacrificing performance. Hence, this paper has two main contributions. First, two novel parameter-free neighborhood structures named Topological Nearest-Better (TNB) neighborhood and Distance-based Nearest-Better (DNB) neighborhood are proposed in the topological space and decision space, respectively. Second, two proposed neighborhoods are combined with Fuzzy PSO (FPSO) and two novel niching algorithms, called TNB-FPSO and DNB-FPSO, are proposed for solving multimodal optimization problems. It should be noted that we use a zero-order fuzzy system to balance between exploration and exploitation in the proposed algorithms. To evaluate the performance of proposed algorithms, we performed a detailed empirical evaluation on the several standard multimodal benchmark functions. Our results show that DNB-FPSO statistically outperforms the other compared multimodal optimization algorithms.
کلیدواژه‌ها
Particle swarm optimization؛ topological nearest-better neighborhood؛ distance-based nearest-better neighborhood؛ multimodal optimization؛ fuzzy balancer
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