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2013 | 4(30) | 279-289

Article title

Effectiveness of hybrid optimization methods in solving test problems and practical issues

Content

Title variants

Languages of publication

PL EN

Abstracts

EN
This paper shows the results of analyzing the effectiveness and efficiency of a hybrid approach against a variety of optimization problems. An application with a serial-optimization structure, consisting of several methods with different characteristics, is presented. In order to evaluate the initial effectiveness of the hybrid optimization method, a number of test tasks, represented by complex functions with many variables, were examined. Additionally, a real-life case, determining an optimal product variety in a supermarket environment, regarding the highest rate of return for given conditions and limitations, is presented as an instance of the practical use of a hybrid algorithm. The research shows that the results achieved by the hybrid- -optimization method are highly satisfactory, both in terms of efficiency as well as effectiveness.

Keywords

Year

Issue

Pages

279-289

Physical description

Contributors

  • Zachodniopomorski Uniwersytet Technologiczny w Szczecinie
author
  • Zachodniopomorski Uniwersytet Technologiczny w Szczecinie
author
  • Instytut Badania Ryzyk i Zagrożeń sp. z o.o., sp. k.
author
  • Zachodniopomorski Uniwersytet Technologiczny w Szczecinie

References

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  • Białynicki-Birula I., Realisty Modeling, Prószyński i S-ka, Warszawa 2002.
  • L’Ecuyer P., Lemieux C., Recent Advances in Randomized Quasi-Monte Carlo Methods, Kluwer Academic Publishers, Boston 2002.
  • Findeisen W., Szymanowski J., Wierzbicki A., Theory and computational methods of optimization (in Polish), PWN, Warszawa 1980.
  • Gondzio J., Grothey A., Solving Nonlinear Portfolio Optimization Problems with the Primal-Dual Interior Point Method , Technical Report MS 2004-001, School of Mathematics, Edinburgh University, 2004.
  • De Jong K.A., Genetic Algorithms Are NOT Function Optimizers, Foundations of Genetic Algorithms, Morgan Kaufmann Publishers, 1993.
  • Pietruszkiewicz W., Twardochleb M., Roszkowski M., Hybrid approach to supporting decision making processes in companies, “Control and Cybernetics” 2011, vol. 40 (1/2011).
  • Pinter J.D., Handbook of Global Optimization, vol. 2, Global Optimization: Software, Test Problems, and Applications, Kluwer Academic Publishers, 2002.
  • Rogowski W., The Efficiency of Investment (in Polish), Wolters Kluwer Polska, Warszawa 2008.
  • Rust J., Using Randomization to Break the Curse of Dimensionality, Yale University, 1996.
  • SOMA − Self-Organizing Migrating Algorithm & Differential Evolution (DE)Test functions, http://www.ft.utb.cz/people/zelinka/soma/func.html [accessed: April 2012].
  • Twardochleb M., Rychcicki R., Efficiency of hybrid optimization method in solving tasks of varied characteristics (in Polish), “Methods of Applied IT” 2009, no. 4, Szczecin.
  • Twardochleb M., Włoch P., Supporting the decision making process for a model of investment issues with the use of the Monte Carlo simulation (in Polish), [in:] Information Technology. Problems and Applications, University of Szczecin, Szczecin 2010.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-b9905fe3-0dfd-47e3-a8cb-221309d5d467
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