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Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds
Joint Authors
Gajdos, Petr
Uher, Vojtěch
Radecký, Michal
Snášel, Václav
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-11-15
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price.
It is popular for its simplicity and robustness.
This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed.
The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants.
However, the DE has a great potential in the spatial data analysis and pattern recognition.
This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions.
It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs).
The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs.
The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population.
A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced.
The algorithm is tested on several spatial datasets and optimization problems.
The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.
American Psychological Association (APA)
Uher, Vojtěch& Gajdos, Petr& Radecký, Michal& Snášel, Václav. 2016. Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1099727
Modern Language Association (MLA)
Uher, Vojtěch…[et al.]. Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1099727
American Medical Association (AMA)
Uher, Vojtěch& Gajdos, Petr& Radecký, Michal& Snášel, Václav. Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1099727
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099727