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RESEARCH ARTICLE

End of day process optimization through multi-mode resource constrained project scheduling - A banking case study

Ezgi Karabulut Türkseven1* ,  Ezgi Genç1 ,  Ilgın Şafak2
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1 Department of Industrial Engineering, Sabanci University, Istanbul, Turkey
2 Fibabanka R&D Center, Istanbul, Turkey
IJOCTA, 1694 https://doi.org/10.36922/ijocta.1694
Submitted: 29 September 2024 | Accepted: 8 February 2025 | Published: 8 April 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

An End-of-Day process is a batch job that includes a sequence of programs, wherein tasks are completed automatically at times specified by a scheduler. The efficient allocation of resources for the timely execution of tasks allows a company to reduce the overall time needed for the completion of the work and improve customer satisfaction by delivering orders on time. This paper presents a case study of a Turkish bank with the objective of minimizing the duration of the end-of-day process through the optimization of work scheduling and resource allocation. This problem is modeled as a multi-mode resource constrained project scheduling problem, optimally resolved by mixed-integer programming, and approximated via simulated annealing heuristic. The scheduler in this paper can also be used to assess the importance of scheduling and crashing tasks, along with the sufficiency of the infrastructure to optimize the End-of-Day process.

Keywords
Multi-mode resource constrained project scheduling
Thread allocation
Simulated annealing
End of Day process optimization
Banking case study
Funding
This research has been funded by Fibabanka, with grant number E.D.VR-21-02416.
Conflict of interest
The authors declare that they have no conflict of interest regarding the publication of this article.
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An International Journal of Optimization and Control: Theories & Applications, Electronic ISSN: 2146-5703 Print ISSN: 2146-0957, Published by AccScience Publishing
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