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research-article

A framework for modeling and executing task-Specific resource allocations in business processes

Authors:

Maximilian Völker,

Mathias WeskeAuthors Info & Claims

Computing, Volume 104, Issue 11

Pages 2405 - 2429

https://doi.org/10.1007/s00607-022-01093-2

Published: 01 November 2022 Publication History

Abstract

As resources are valuable assets, organizations have to decide which resources to allocate to business process tasks in a way that the process is executed not only effectively but also efficiently. Traditional role-based resource allocation leads to effective process executions, since each task is performed by a resource that has the required skills and competencies to do so. However, the resulting allocations are typically not as efficient as they could be, since optimization techniques have yet to find their way in traditional business process management scenarios. On the other hand, operations research provides a rich set of analytical methods for supporting problem-specific decisions on resource allocation. This paper provides a novel framework for creating transparency on existing tasks and resources, supporting individualized allocations for each activity in a process, and the possibility to integrate problem-specific analytical methods of the operations research domain. To validate the framework, the paper reports on the design and prototypical implementation of a software architecture, which extends a traditional process engine with a dedicated resource management component. This component allows us to define specific resource allocation problems at design time, and it also facilitates optimized resource allocation at run time. The framework is evaluated using a real-world parcel delivery process. The evaluation shows that the quality of the allocation results increase significantly with a technique from operations research in contrast to the traditional applied rule-based approach.

References

[1]

Arias M, Munoz-Gama J, Sepúlveda M, and Miranda JC Human resource allocation or recommendation based on multi-factor criteria in on-demand and batch scenarios Eur J Ind Eng 2018 12 3 364-404

[2]

Arias M, Saavedra R, Marques MR, Munoz-Gama J, and Sepúlveda M Human resource allocation in business process management and process mining: A systematic mapping study Manag Decis 2018 56 2 376-405

[3]

Bang-Jensen J, Gutin G, and Yeo A When the greedy algorithm fails Discret Optim 2004 1 2 121-127

[4]

Bellaaj Elloumi F, Sellami M, and Bhiri S Avoiding resource misallocations in business processes Concurrency and Computation: Practice and Experience 2018 32

[5]

Cabanillas C (2016) Process-and resource-aware information systems. In: EDOC, 2016 IEEE 20th International, IEEE, p 1–10

[6]

Cabanillas C, García JM, Resinas M, Ruiz D, Mendling J, Ruiz-Cortés A (2013) Priority-based human resource allocation in business processes. In: ICSOC, Springer, 374–388

[7]

Djedovic A, Karabegovic A, Avdagic Z, Omanovic S (2018) Innovative approach in modeling business processes with a focus on improving the allocation of human resources. Math Probl Eng

[8]

Doerner K, Gutjahr WJ, Kotsis G, Polaschek M, and Strauss C Enriched workflow modelling and stochastic branch-and-bound Eur J Oper Res 2006 175 3 1798-1817

[9]

Dumas M, La Rosa M, Mendling J, Reijers HA, et al. Fundamentals of business process management, 2013 Berlin Springer

[10]

Durán F, Rocha C, and Salaün G A rewriting logic approach to resource allocation analysis in business process models Sci Comput Program 2019 183

[11]

Ha BH, Bae J, Park YT, and Kang SH Development of process execution rules for workload balancing on agents Data & Knowl Eng 2006 56 1 64-84

[12]

Havur G, Cabanillas C, Mendling J, Polleres A (2016) Resource allocation with dependencies in business process management systems. In: BPM, Springer, pp 3–19

[13]

Hirsch MJ and Ortiz-Peña H Information supply chain optimization with bandwidth limitations Int Trans Oper Res 2017 24 5 993-1022

[14]

Huang Z, van der Aalst WM, Lu X, and Duan H An adaptive work distribution mechanism based on reinforcement learning Expert Syst Appl 2010 37 12 7533-7541

[15]

Huang Z, van der Aalst WM, Lu X, and Duan H Reinforcement learning based resource allocation in business process management Data & Knowl Eng 2011 70 1 127-145

[16]

Huang Z, Lu X, and Duan H A task operation model for resource allocation optimization in business process management IEEE Transactions on Systems, man, and cybernetics-part a: systems and humans 2012 42 5 1256-1270

[17]

Ihde S, Pufahl L, Lin MB, Goel A, Weske M (2019) Optimized resource allocations in business process models. In: Business Process Management Forum. BPM 2019., Springer International Publishing, Cham, pp 55–71

[18]

Kamrani F, Ayani R, and Moradi F A framework for simulation-based optimization of business process models SIMULATION 2012 88 7 852-869

[19]

Kuhn HW The hungarian method for the assignment problem Naval research logistics quarterly 1955 2 1–2 83-97

[20]

Kumar A, Van Der Aalst WM, and Verbeek EM Dynamic work distribution in workflow management systems: How to balance quality and performance J Manag Inf Syst 2002 18 3 157-193

[21]

Kumar A, Dijkman R, Song M (2013) Optimal resource assignment in workflows for maximizing cooperation. In: BPM, Springer, pp 235–250

[22]

Liu T, Cheng Y, and Ni Z Mining event logs to support workflow resource allocation Knowl-Based Syst 2012 35 320-331

[23]

OMG (2011) Notation BPMN version 2.0. OMG Specification, Object Management Group pp 22–31

[24]

Pellerin R, Perrier N, Berthaut F (2019) A survey of hybrid metaheuristics for the resource-constrained project scheduling problem. EJOR

[25]

Pflug J and Rinderle-Ma S Application of dynamic instance queuing to activity sequences in cooperative business process scenarios Int J Coop 2016 25 01 1650002

[26]

Pufahl L, Ihde S, Glöckner M, Franczyk B, Paulus B, Weske M (2020) Countering congestion: A white-label platform for the last mile parcel delivery. In: 23rd BIS Conference, Springer, pp 210–223

[27]

Pufahl L, Ihde S, Stiehle F, Weske M, Weber I (2021) Automatic resource allocation in business processes: A systematic literature survey. arXiv:2107.07264

[28]

Reijers HA, Jansen-Vullers MH, Zur Muehlen M, Appl W (2007) Workflow management systems+ swarm intelligence= dynamic task assignment for emergency management applications. In: BPM, Springer, pp 125–140

[29]

Rhee SH, Cho NW, and Bae H Increasing the efficiency of business processes using a theory of constraints ISF 2010 12 4 443-455

[30]

Russell N, van der Aalst WMP, ter Hofstede AH, Edmond D (2005) Workflow resource patterns: Identification, representation and tool support. In: CAiSE, Springer, pp 216–232

[31]

Schönig S, Cabanillas C, Jablonski S, and Mendling J A framework for efficiently mining the organisational perspective of business processes Decis Support Syst 2016 89 87-97

[32]

Tanenbaum A (2009) Modern operating systems. Pearson Education, Inc.,

[33]

Toth P, Vigo D (2014) Vehicle Routing: Problems, Methods, and Applications. No. 18 in MOS-SIAM Series on Optimization, SIAM

[34]

Van Hee K, Reijers H, Verbeek H, Zerguini L (2001) On the optimal allocation of resources in stochastic workflow nets. In: UK Performance Engineering Workshop, Print Services University of Leeds, pp 23–34

[35]

Weske M Business Process Management - Concepts, Languages, Architectures 2019 3 Berlin Springer

[36]

Xu J, Liu C, Zhao X (2009) Resource planning for massive number of process instances. In: CooPIS Conference, Springer, pp 219–236

[37]

Xu J, Liu C, Zhao X, Yongchareon S, and Ding Z Resource management for business process scheduling in the presence of availability constraints ACM TMIS 2016 7 3 1-26

[38]

Yaghoibi M and Zahedi M Cycle time reduction and runtime rebalancing by reallocating dependent tasks Int J Eng 2017 30 12 1831-1839

Cited By

Fattouch NBen Lahmar IBoukadi K(2025)Context-aware resource allocation for IoRT-aware business processes based on decentralized multi-agent reinforcement learningCluster Computing10.1007/s10586-024-04760-528:1Online publication date: 1-Feb-2025
https://dl.acm.org/doi/10.1007/s10586-024-04760-5
Wang JYu DLiu C(2024)Task allocation for maximum cooperation in complex structured business processesKnowledge-Based Systems10.1016/j.knosys.2024.111989299:COnline publication date: 5-Sep-2024
https://dl.acm.org/doi/10.1016/j.knosys.2024.111989
Padella AMannhardt FVinci Fde Leoni MVanderfeesten I(2024)Experience-Based Resource Allocation for Remaining Time OptimizationBusiness Process Management10.1007/978-3-031-70396-6_20(345-362)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-70396-6_20
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Information

Published In

cover image Computing

Computing Volume 104, Issue 11

Nov 2022

189 pages

ISSN:0010-485X

Issue’s Table of Contents

© The Author(s) 2022.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 November 2022

Accepted: 11 May 2022

Received: 08 September 2021

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Bundesministerium für Wirtschaft und Energie

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Cited By

Fattouch NBen Lahmar IBoukadi K(2025)Context-aware resource allocation for IoRT-aware business processes based on decentralized multi-agent reinforcement learningCluster Computing10.1007/s10586-024-04760-528:1Online publication date: 1-Feb-2025
https://dl.acm.org/doi/10.1007/s10586-024-04760-5
Wang JYu DLiu C(2024)Task allocation for maximum cooperation in complex structured business processesKnowledge-Based Systems10.1016/j.knosys.2024.111989299:COnline publication date: 5-Sep-2024
https://dl.acm.org/doi/10.1016/j.knosys.2024.111989
Padella AMannhardt FVinci Fde Leoni MVanderfeesten I(2024)Experience-Based Resource Allocation for Remaining Time OptimizationBusiness Process Management10.1007/978-3-031-70396-6_20(345-362)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-70396-6_20
Schumann FRinderle-Ma S(2023)Resource-Driven Process Manipulation: Modeling Concepts and Valid AllocationsCooperative Information Systems10.1007/978-3-031-46846-9_23(416-426)Online publication date: 30-Oct-2023
https://dl.acm.org/doi/10.1007/978-3-031-46846-9_23

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