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Probability-based genetic algorithm for solving complex multiobjective optimization tasks using adaptive mutation operator and Pareto set prediction
- Authors: Sopov Y.A.1, Sopov S.A.1
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Affiliations:
- Siberian State Aerospace University
- Issue: Vol 10, No 6 (2011)
- Pages: 273-282
- Section: INFORMATION SCIENCE, COMPUTING TECHNOLOGY AND CONTROL
- URL: https://journals.ssau.ru/vestnik/article/view/7513
- DOI: https://doi.org/10.18287/2541-7533-2011-0-6(30)-273-282
- ID: 7513
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Abstract
The article is devoted to a new algorithm for solving complex constrained multiobjective optimization tasks on the basis of probability-based GA. An efficient modification of the algorithm using adaptive mutation and Pareto set prediction is proposed. The results of efficiency investigation are presented.
About the authors
Ye. A. Sopov
Siberian State Aerospace University
Author for correspondence.
Email: es_gt@mail.ru
candidate of technical sciences, associate professor
Russian FederationS. A. Sopov
Siberian State Aerospace University
Email: sopov_sergey@mail.ru
student
Russian FederationReferences
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