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International Conference on Evolutionary Multi-Criterion Optimization

EMO 2003: Evolutionary Multi-Criterion Optimization pp 752–766Cite as

A Real-World Test Problem for EMO Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2632))

Abstract

In this paper, a real-world test problem is presented and made available for use by the EMO community. The problem deals with the optimization of polymer extrusion, in terms of setting the operating conditions and/or the screw geometry. The binary code of a computer program that predicts the thermomechanical experience of a polymer inside the machine, as a function of geometry, polymer properties and operating conditions, is developed. The program can be used through input and output data files, so that the parameters to optimize and the criteria evaluated data is communicated in both directions. Two distinct EMO algorithms are used to illustrate and test the optimization of this problem.

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Author information

Authors and Affiliations

  1. Dept. of Polymer Engineering, University of Minho, Guimarães, Portugal

    A. Gaspar-Cunha & J. A. Covas

Authors
  1. A. Gaspar-Cunha
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  2. J. A. Covas
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Editor information

Editors and Affiliations

  1. Faculty of Sciences and Technology, Centre for Intelligent Systems, University of the Algarve, Campus de Gambelas, 8005-139, Faro, Portugal

    Carlos M. Fonseca

  2. Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK

    Peter J. Fleming

  3. Department of Electrical Engineering, Computer Engineering and Networks Laboratory, Swiss Federal Institute of Technology, Gloriastraße 35, 8092, Zürich, Switzerland

    Eckart Zitzler  & Lothar Thiele  & 

  4. Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory, Indian Institute of Technology, Kanpur, UP, 208 016, India

    Kalyanmoy Deb

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© 2003 Springer-Verlag Berlin Heidelberg

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Gaspar-Cunha, A., Covas, J.A. (2003). A Real-World Test Problem for EMO Algorithms. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Thiele, L., Deb, K. (eds) Evolutionary Multi-Criterion Optimization. EMO 2003. Lecture Notes in Computer Science, vol 2632. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36970-8_53

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  • DOI: https://doi.org/10.1007/3-540-36970-8_53

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-01869-8

  • Online ISBN: 978-3-540-36970-7

  • eBook Packages: Springer Book Archive

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