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An improved decision support model for scheduling production in an engineer-to-order manufacturer

An improved decision support model for scheduling production in an engineer-to-order manufacturer This paper outlines a mathematical model to solve a scheduling problem for a company engineering and producing propellers to order. Nonås and Olsen (Comput Oper Res 32(9):2351–2382, 2005) have previously introduced a Mixed Integer Programming model for this production setting with the objective of minimizing the total tardiness. The mathematical model could however not be used to solve realistic sized problem instances, because of the very large solution time. We propose a new time indexed formulation that can solve most industrial problem instances in less than 10 min. This work is further extended by taking into account limited storage capacity and by proposing different methods to balance between total tardiness and maximum tardiness. We illustrate how the solution time and the criteria change for different setups of the mathematical model and suggest which setup to use for different scenarios. The paper also discusses how the new model can be extended to include unexpected events such as emergency orders and unavailable production equipment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png 4OR Springer Journals

An improved decision support model for scheduling production in an engineer-to-order manufacturer

Dauzère-Pérès, Stéphane; Nonås, Sigrid Lise
4OR , Volume 21 (2): 54 – Jun 1, 2023
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References (48)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022
ISSN
1619-4500
eISSN
1614-2411
DOI
10.1007/s10288-022-00508-2
Publisher site
See Article on Publisher Site

Abstract

This paper outlines a mathematical model to solve a scheduling problem for a company engineering and producing propellers to order. Nonås and Olsen (Comput Oper Res 32(9):2351–2382, 2005) have previously introduced a Mixed Integer Programming model for this production setting with the objective of minimizing the total tardiness. The mathematical model could however not be used to solve realistic sized problem instances, because of the very large solution time. We propose a new time indexed formulation that can solve most industrial problem instances in less than 10 min. This work is further extended by taking into account limited storage capacity and by proposing different methods to balance between total tardiness and maximum tardiness. We illustrate how the solution time and the criteria change for different setups of the mathematical model and suggest which setup to use for different scenarios. The paper also discusses how the new model can be extended to include unexpected events such as emergency orders and unavailable production equipment.

Journal

4OR – Springer Journals

Published: Jun 1, 2023

Keywords: Scheduling; Engineer-to-order; Optimization; Mathematical modeling; 90B35 Deterministic scheduling theory in operations research; 90C11 Mixed integer programming

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