NDLI: A novel multivariant optimization algorithm for multimodal optimization

Content Provider	IEEE Xplore Digital Library
Author	Changxing Gou Xinling Shi Baolei Li Tiansong Li Lanjuan Liu Qinhu Zhang Yajie Liu
Copyright Year	2013
Description	Author affiliation: Dept. of Electron. Eng., Yunnan Univ., Kunming, China (Changxing Gou; Xinling Shi; Baolei Li; Tiansong Li; Lanjuan Liu; Qinhu Zhang) \|\| Center of Med. Equip., Third Affiliated Hosp. of Kunming Med. Univ. (Yunnan Tumor Hosp.), Kunming, China (Yajie Liu)
Abstract	This paper provides a detailed description of a novel multivariant optimization algorithm (MOA) for multi-modal optimization with the main idea to share search information by organizing all search atoms into a special designed structure. Its multiple and variant group property make MOA capable on multi-modal optimization problems. The capability of the MOA method in locating and maintaining multi optima in one execution is discussed in details in this paper and two experiments are carried out to validate its feasibility in multi-modal optimization problems. The experimental results are also compared with those obtained by the species-based PSO, the adaptive sequential niche PSO and the memetic PSO. The experiment results show that MOA has high success rate and convergence speed in multi-modal optimization problems.
Sponsorship	IEEE Eng.Med. Biol. Soc.
Starting Page	1623
Ending Page	1627
File Size	670948
Page Count	5
File Format	PDF
e-ISBN	9781479927647
DOI	10.1109/CISP.2013.6743936
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Accuracy search atom orderd-list Heuristic algorithms Sociology multi-modal optimization Statistics Optimization Convergence
Content Type	Text
Resource Type	Article

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