InterCriteria Analysis Approach for Comparison of Simple and Multi-population Genetic Algorithms Performance-Reference-Cited by-同舟云学术

InterCriteria Analysis Approach for Comparison of Simple and Multi-population Genetic Algorithms Performance

Published:2018-09-19 Issue: Volume: Page:117-130
ISSN:1860-949X
Container-title:Recent Advances in Computational Optimization
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Author:

Angelova Maria,Pencheva Tania

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-99648-6_7

Reference22 articles.

1. Angelova, M., Pencheva, T.: Genetic operators significance assessment in multi-population genetic algorithms. Int. J. of Metaheuristics 3(2), 162–173 (2014)

2. Angelova, M., Tzonkov, S., Pencheva, T.: Modified multi-population genetic algorithm for yeast fed-batch cultivation parameter identification. Int. J. Bioautomation 13(4), 163–172 (2009)

3. Angelova, M., Pencheva, T.: InterCriteria analysis of multi-population genetic algorithms performance. Ann. Comp. Sci. Inf. Syst. 13, 77–82 (2017)

4. Angelova, M., Melo-Pinto, P., Pencheva, T.: Modified simple genetic algorithms improving convergence time for the purposes of fermentation process parameter Identification. WSEAS Trans. Syst. 11(7), 256–267 (2012)

5. Angelova, M., Tzonkov, S., Pencheva, T.: Genetic algorithms based parameter identification of yeast fed-batch cultivation. Lect. Notes Comput. Sci. 6046, 224–231 (2011)

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