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Abstract
Paper presents a computational optimization study using a genetic gender approach for solving multi-objective optimization problems of detection observers. In this methodology the information about an individual gender of all the considered solutions is applied for the purpose of making distinction between different groups of objectives. This information is drawn out of the fitness of individuals and applied during a current parental crossover in the performed evolutionary multi-objective optimization (EMO) processes.
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- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- The 12th International Conference on Diagnostics of Processes and Systems (DPS’2015) strony 1 - 12
- Language:
- English
- Publication year:
- 2015
- Bibliographic description:
- Białaszewski T., Kowalczuk Z.: Solving highly-dimensional multi-objective optimization problems by means of genetic gender// The 12th International Conference on Diagnostics of Processes and Systems (DPS’2015)/ ed. ./IPCChair: Kowalczuk Zdzisław Polska: PAN, POLSPAR, GUT, UZ, WUT, 2015, s.1-12
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-319-23180-8_23
- Verified by:
- Gdańsk University of Technology
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