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Open Access Journal Article

Simulation-based Optimization for Production Systems

by Michael Thomas 1,*
1
Michael Thomas
*
Author to whom correspondence should be addressed.
ORS  2022 4(2):35; https://doi.org/10.69610/j.ors.20221215
Received: 14 October 2022 / Accepted: 25 November 2022 / Published Online: 15 December 2022
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Abstract

Simulation-based optimization (SBO) has emerged as a powerful tool for enhancing production system performance. This paper explores the application of SBO techniques in optimizing production systems, focusing on the integration of simulation models with optimization algorithms. By leveraging the ability to model complex production processes, SBO provides a means to identify optimal operational parameters and configurations that can lead to improved efficiency, productivity, and cost-effectiveness. The study delves into various SBO approaches, including genetic algorithms, particle swarm optimization, and evolutionary strategies, which are employed to address production system challenges such as capacity planning, resource allocation, and scheduling problems. Through a series of case studies, the effectiveness of SBO in optimizing production systems is demonstrated, highlighting the benefits of incorporating simulation-based approaches into the decision-making process for production management.

Keywords: Simulation-based optimization (SBO); Production systems; Genetic algorithms; Particle swarm optimization; Optimization algorithms.;
Copyright: © 2022 by Thomas. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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APA Style
Thomas, M. (2022). Simulation-based Optimization for Production Systems. Operations Research and Statistics, 4(2), 35. doi:10.69610/j.ors.20221215
ACS Style
Thomas, M. Simulation-based Optimization for Production Systems. Operations Research and Statistics, 2022, 4, 35. doi:10.69610/j.ors.20221215
AMA Style
Thomas M. Simulation-based Optimization for Production Systems. Operations Research and Statistics; 2022, 4(2):35. doi:10.69610/j.ors.20221215
Chicago/Turabian Style
Thomas, Michael 2022. "Simulation-based Optimization for Production Systems" Operations Research and Statistics 4, no.2:35. doi:10.69610/j.ors.20221215

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ACS Style
Thomas, M. Simulation-based Optimization for Production Systems. Operations Research and Statistics, 2022, 4, 35. doi:10.69610/j.ors.20221215
AMA Style
Thomas M. Simulation-based Optimization for Production Systems. Operations Research and Statistics; 2022, 4(2):35. doi:10.69610/j.ors.20221215
Chicago/Turabian Style
Thomas, Michael 2022. "Simulation-based Optimization for Production Systems" Operations Research and Statistics 4, no.2:35. doi:10.69610/j.ors.20221215
APA style
Thomas, M. (2022). Simulation-based Optimization for Production Systems. Operations Research and Statistics, 4(2), 35. doi:10.69610/j.ors.20221215

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