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Problems of a Utopia Point Setting in Transformation of Individual Objective Functions in Multi-Objective Optimization

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  • Važan Pavel

    (Slovak University of Technology in Bratislava, Faculty of Materials Science and Technology in Trnava, Institute of Applied Informatics, Automation and Mechatronics, Ulica Jána Bottu 2781/25, 917 24Trnava Slovak Republic)

  • Červeňanská Zuzana

    (Slovak University of Technology in Bratislava, Faculty of Materials Science and Technology in Trnava, Institute of Applied Informatics, Automation and Mechatronics, Ulica Jána Bottu 2781/25, 917 24Trnava Slovak Republic)

  • Kotianová Janette

    (Slovak University of Technology in Bratislava, Faculty of Materials Science and Technology in Trnava, Institute of Applied Informatics, Automation and Mechatronics, Ulica Jána Bottu 2781/25, 917 24Trnava Slovak Republic)

  • Holík Jiří

    (Dynamic Future, S.R.O., Občanská 1117/23, 710 00Ostrava, Czech Republic)

Abstract

In an optimal processes control, where the considered goals are in general observed as concurrently conflicted, a multi-objective approach fits the best. Commonly used scalarization techniques in multi-objective optimization need a transformation of the individual single-objective functions involved into a scalar multi-criteria objective function. There are many parameters which can influence the optimization results solutions, including an unreachable utopia point value. In this study, the authors compare the multi-objective problem solutions found via two ways of the individual objectives transformation with the respect to setting the utopia point. The methods are used in the area of production control in a case study for a batch production system. To find the solutions, The Weighted Sum Method with a priori articulated preferences under specific constraints as the scalar multi-objective optimization method is applied in simulation optimization.

Suggested Citation

  • Važan Pavel & Červeňanská Zuzana & Kotianová Janette & Holík Jiří, 2019. "Problems of a Utopia Point Setting in Transformation of Individual Objective Functions in Multi-Objective Optimization," Research Papers Faculty of Materials Science and Technology Slovak University of Technology, Sciendo, vol. 27(45), pages 64-71, September.
    • Handle: RePEc:vrs:repfms:v:27:y:2019:i:45:p:64-71:n:9
    DOI: 10.2478/rput-2019-0027
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    References listed on IDEAS

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    1. Satyajith Amaran & Nikolaos V. Sahinidis & Bikram Sharda & Scott J. Bury, 2016. "Simulation optimization: a review of algorithms and applications," Annals of Operations Research, Springer, vol. 240(1), pages 351-380, May.
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