Statistical Design of Genetic Algorithms for Combinatorial Optimization Problems
Joint Authors
Najafi, Amir Abbas
Niaki, Seyed Taghi Akhavan
Shahsavar, Moslem
Source
Mathematical Problems in Engineering
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-09-11
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Many genetic algorithms (GA) have been applied to solve different NP-complete combinatorial optimization problems so far.
The striking point of using GA refers to selecting a combination of appropriate patterns in crossover, mutation, and and so forth and fine tuning of some parameters such as crossover probability, mutation probability, and and so forth.
One way to design a robust GA is to select an optimal pattern and then to search for its parameter values using a tuning procedure.
This paper addresses a methodology to both optimal pattern selection and the tuning phases by taking advantage of design of experiments and response surface methodology.
To show the performances of the proposed procedure and demonstrate its applications, it is employed to design a robust GA to solve a project scheduling problem.
Through the statistical comparison analyses between the performances of the proposed method and an existing GA, the effectiveness of the methodology is shown.
American Psychological Association (APA)
Shahsavar, Moslem& Najafi, Amir Abbas& Niaki, Seyed Taghi Akhavan. 2011. Statistical Design of Genetic Algorithms for Combinatorial Optimization Problems. Mathematical Problems in Engineering،Vol. 2011, no. 2011, pp.1-17.
https://search.emarefa.net/detail/BIM-505106
Modern Language Association (MLA)
Shahsavar, Moslem…[et al.]. Statistical Design of Genetic Algorithms for Combinatorial Optimization Problems. Mathematical Problems in Engineering No. 2011 (2011), pp.1-17.
https://search.emarefa.net/detail/BIM-505106
American Medical Association (AMA)
Shahsavar, Moslem& Najafi, Amir Abbas& Niaki, Seyed Taghi Akhavan. Statistical Design of Genetic Algorithms for Combinatorial Optimization Problems. Mathematical Problems in Engineering. 2011. Vol. 2011, no. 2011, pp.1-17.
https://search.emarefa.net/detail/BIM-505106
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-505106