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Open AccessArticle

Multi-Objective Optimization of Production Objectives Based on Surrogate Model

Faculty of Materials Science and Technology in Trnava, Slovak University of Technology in Bratislava, 91724 Trnava, Slovakia
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Appl. Sci. 2020, 10(21), 7870; https://doi.org/10.3390/app10217870
Received: 18 September 2020 / Revised: 2 November 2020 / Accepted: 3 November 2020 / Published: 6 November 2020
The article addresses an approximate solution to the multi-objective optimization problem for a black-box function of a manufacturing system. We employ the surrogate of the discrete-event simulation model of a batch production system in an analytical form. Integration of simulation, Design of Experiments methods, and Weighted Sum and Weighted Product multi-objective methods are used in an arrangement of a priori defined preferences to find a solution near the Pareto optimal solution in a criterion space. We compare the results obtained through the analytical approach to the outcomes of simulation-based optimization. The observed results indicate a possibility to apply the suitable analytical model for quickly finding the acceptable approximate solution close to the Pareto optimal front. View Full-Text
Keywords: multi-objective optimization; metamodel; surrogate model; manufacturing system; simulation-based optimization multi-objective optimization; metamodel; surrogate model; manufacturing system; simulation-based optimization
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MDPI and ACS Style

Červeňanská, Z.; Kotianová, J.; Važan, P.; Juhásová, B.; Juhás, M. Multi-Objective Optimization of Production Objectives Based on Surrogate Model. Appl. Sci. 2020, 10, 7870.

AMA Style

Červeňanská Z, Kotianová J, Važan P, Juhásová B, Juhás M. Multi-Objective Optimization of Production Objectives Based on Surrogate Model. Applied Sciences. 2020; 10(21):7870.

Chicago/Turabian Style

Červeňanská, Zuzana; Kotianová, Janette; Važan, Pavel; Juhásová, Bohuslava; Juhás, Martin. 2020. "Multi-Objective Optimization of Production Objectives Based on Surrogate Model" Appl. Sci. 10, no. 21: 7870.

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