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The Expanded Invasive Weed Optimization Metaheuristic for Solving Continuous and Discrete Optimization Problems
Joint Authors
Josiński, Henryk
Kostrzewa, Daniel
Michalczuk, Agnieszka
Świtoński, Adam
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-19
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
This paper introduces an expanded version of the Invasive Weed Optimization algorithm (exIWO) distinguished by the hybrid strategy of the search space exploration proposed by the authors.
The algorithm is evaluated by solving three well-known optimization problems: minimization of numerical functions, feature selection, and the Mona Lisa TSP Challenge as one of the instances of the traveling salesman problem.
The achieved results are compared with analogous outcomes produced by other optimization methods reported in the literature.
American Psychological Association (APA)
Josiński, Henryk& Kostrzewa, Daniel& Michalczuk, Agnieszka& Świtoński, Adam. 2014. The Expanded Invasive Weed Optimization Metaheuristic for Solving Continuous and Discrete Optimization Problems. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1051248
Modern Language Association (MLA)
Josiński, Henryk…[et al.]. The Expanded Invasive Weed Optimization Metaheuristic for Solving Continuous and Discrete Optimization Problems. The Scientific World Journal No. 2014 (2014), pp.1-14.
https://search.emarefa.net/detail/BIM-1051248
American Medical Association (AMA)
Josiński, Henryk& Kostrzewa, Daniel& Michalczuk, Agnieszka& Świtoński, Adam. The Expanded Invasive Weed Optimization Metaheuristic for Solving Continuous and Discrete Optimization Problems. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1051248
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051248