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Optimal Design of Multiple Clutch Brakes Using a Multistage Evolutionary Method

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IUTAM Symposium on Evolutionary Methods in Mechanics

Part of the book series: Solid Mechanics and Its Applications ((SMIA,volume 117))

Abstract

In the paper an optimization problem of design of multiple clutch brakes is presented. The problem has a multicriteria character in which there are four objective functions and several constraints. To solve this problem a multistage approach to multicriteria design optimization is proposed. At all stages bicriteria optimization models are solved using evolutionary algorithms. After solving each model the set of Pareto optimal solutions is generated and can be graphically illustrated in the space of objectives. Then this set is presented to the designer who decides on which level one of the objective functions is treated as the constraint. The process is repeated till all the objective functions are considered.

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References

  1. Coello C.A.C, Veldhuizen D. and Lamont G.: Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academic Publisher, New York, 2002.

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  2. Deb K.: Multi-objective Optimization Using evolutionary Algorithms. Wiley & Sons, Chichester, New York, 2001.

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  3. Osyczka A.: Evolutionary Algorithms for Single and Multicriteria Design Optimization. Springer Physica-Verlag, Heilderberg, Berlin, 2002.

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  4. Osyczka A. and Krenich S.: A New Constraint Tournament Selection Method for Multicriteria Optimization Using Genetic Algorithm. [In:] Proc. of the Congress of Evolutionary Computing, San Diego, USA, pp. 501–509, 2000.

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© 2004 Kluwer Academic Publishers

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Krenich, S., Osyczka, A. (2004). Optimal Design of Multiple Clutch Brakes Using a Multistage Evolutionary Method. In: Burczyński, T., Osyczka, A. (eds) IUTAM Symposium on Evolutionary Methods in Mechanics. Solid Mechanics and Its Applications, vol 117. Springer, Dordrecht. https://doi.org/10.1007/1-4020-2267-0_21

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  • DOI: https://doi.org/10.1007/1-4020-2267-0_21

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-2266-1

  • Online ISBN: 978-1-4020-2267-8

  • eBook Packages: Springer Book Archive

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