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An improved similarity based adaptive step size glowworm algorithm
School of Information Engineering, East China Jiaotong University.
School of Information Engineering, East China Jiaotong University.
Department of Business and Computer Science, Southwestern Oklahoma State University.
College of Computer and Information Sciences, Almuzahmiyah, King Saud University.
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2015 (English)In: Journal of Internet Technology, ISSN 1607-9264, E-ISSN 2079-4029, Vol. 16, no 5, p. 905-914Article in journal (Refereed) Published
Abstract [en]

This paper presents the similarity based adaptive step size glowworm swarm optimization algorithm (SBASS-GSO), an improved version of glowworm swarm optimization algorithm (GSO). The standard GSO algorithm lacks unified metric standard to different problems in the selection of neighbor set, which makes the algorithm converge slowly because of improper selection. Because the step size s is fixed, the oscillation phenomenon may occur in local search space, which leads to inferior search accuracy In SBASS-GSO algorithm, we change neighborhood definition base on the similarity not on the distance. The neighborhood is selected by computing average similarity, which provides priori knowledge for the adaptive size s. The dynamic size s is useful for removing oscillation phenomenon and improving the convergence speed. Experimental results demonstrate the efficacy of the proposed glowworm algorithm in capturing multiple optima of a series of complex test functions, such as Zakharov and Sphere functions. We also provide some comparisons of SBASS-GSO with GSO and verify the superiority in the precision and convergence speed.

Place, publisher, year, edition, pages
2015. Vol. 16, no 5, p. 905-914
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-14115DOI: 10.6138/JIT.2015.16.5.20150618bISI: 000362465600019Scopus ID: 2-s2.0-84943545346Local ID: d706cec4-e593-460e-8e02-c2bedba7dbc8OAI: oai:DiVA.org:ltu-14115DiVA, id: diva2:987069
Note
Validerad; 2015; Nivå 2; 20151019 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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