Abstract
In the process of research, the authors described a computational method for synthesizing solutions to problems of multi-criteria optimization (based on the use of parallel computing) and decision-making with a priori data uncertainty, based on a memetic algorithm that implements the joint use of an evolutionary method with parameters changing from generation to generation: coding, fitness and relaxation functions, Decremental Neighborhood Method, and the random path generation method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Tronchuk, A., Ugryumova, K.: Mathematical models and evolutionary method for solving stochastic optimization problems. J. Kharkiv Nat. Univ. Ser. Math. Model. Inf. Technol. Autom. Control Syst. 19(1015), 292–305 (2012)
Ugryumov, M., Strelets, V., Tronchuk, A., Ugryumova, K., et al.: System improvement of elements of complex technical systems based on the concept of inverse problems. Nat. Aerosp. Univ. Kharkiv (2013). (Cиcтeмнoe coвepшeнcтвoвaниe элeмeнтoв cлoжныx тexничecкиx cиcтeм нa ocнoвe кoнцeпции oбpaтныx зaдaч [Teкcт]: мoнoгpaфия/ B.E. Cтpeлeц, A.A.Tpoнчyк, E.M.Угpюмoвa и дp.; пoд oбщ. peд. M. Л. Угpюмoвa. – X.: Haц. aэpoкocм. yн-т им. H. E. Жyкoвcкoгo « Xapьк. aвиaц. ин-т » , 2013. – 148c. ISBN 978-966-662-312-9
Mazorchuk, M., Parfeniuk, Y., Dobriak, V., Meniailov, I., Chumachenko, D.: Stochastic modelling of cash flow for personal insurance fund using the cloud data storage. Int. J. Comput. 3(17), 153–162 (2018)
Ugryumov, M., Tronchuk, A., Afanasjevska, V., Myenyaylov, A.: Gas turbine engine elements systematic improvement on the base of inverse problem concept by stochastic optimization methods. In: Abstracts Book and CD–ROM Proceedings of the 20-th ISABE Conference, Gothenburg, pp. 673–681 (2011)
Ugryumov, M., Afanasjevska, V., Tronchuk, A., Myenyaylov, A.: Stochastic optimization models and method in the turbomachines system improvement problem. In: Program and CD–ROM Proceedings of ASME-JSME-KSME Joint Fluids Engineering Conference (AJK2011-FED), Hamamatsu, pp. 755–761 (2011)
Ugryumova, K., Chernysh, S., Meniailov, I., Ugryumov, M.: A method synthesis of selection function scalar convolutions for the multi-objective decision-making problems with a priori uncertain data. J. Kharkiv Nat. Univ. Ser.: Math. Model. Inf. Technol. Autom. Control Syst. 27, 172–180 (2015)
Dakota. https://dakota.sandia.gov/
Ipopt (Interior Point OPTimizer). https://projects.coin-or.org/Ipopt
SHERPA: A Python Hyperparameter Optimization Library. https://parameter-sherpa.readthedocs.io/en/latest/#
Meniailov, I., Khustochka, O., Ugryumova, K., Chernysh, S., Yepifanov, S., Ugryumov, M.: Mathematical models and methods of effective estimation in multi-objective optimization problems under uncertainties. In: Advances in Structural and Multidisciplinary Optimization: Proceedings of the 12th World Congress of Structural and Multidisciplinary Optimization (WCSMO12) By Axel Schumacher, pp. 411–427. Springer, Braunschweig (2018)
Karpenko, A.: Modern algorithms of search optimization. Algorithms inspired by nature. The Bauman University Publishing House, Moscow (2014). (A. П. Кapпeнкo. Coвpeмeнныe aлгopитмы пoиcкoвoй oптимизaции. Aлгopитмы, вдoxнoвлeнныe пpиpoдoй. Mocквa: Издaтeльcтвo MГTУ им. H. Э. Бayмaнa, 2014)
Ford, B., Ruebbelke, L.: AngularJS in Action. University of Michigan, Manning (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Meniailov, I., Krivtsov, S., Ugryumov, M., Bazilevich, K., Trofymova, I. (2020). Application of Parallel Computing in Robust Optimization Design. In: Nechyporuk, M., Pavlikov, V., Kritskiy, D. (eds) Integrated Computer Technologies in Mechanical Engineering. Advances in Intelligent Systems and Computing, vol 1113. Springer, Cham. https://doi.org/10.1007/978-3-030-37618-5_44
Download citation
DOI: https://doi.org/10.1007/978-3-030-37618-5_44
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-37617-8
Online ISBN: 978-3-030-37618-5
eBook Packages: EngineeringEngineering (R0)