Systematic Exploitation of Parallel Task Execution in Business Processes

Konstantinos Varvoutas1, Georgia Kougka1 and Anastasios Gounaris1

  1. Department Of Informatics, Aristotle University of Thessaloniki
    Thessaloniki, Greece


Business process re-engineering (or optimization) has been attracting a lot of interest, and it is considered as a core element of business process management (BPM). One of its most effective mechanisms is task re-sequencing with a view to decreasing process duration and costs, whereas duration (aka cycle time) can be reduced using task parallelism as well. In this work, we propose a novel combination of these two mechanisms, which is resource allocation-aware. Starting from a solution where a given resource allocation in business processes can drive optimizations in an underlying BPMN diagram, our proposal considers resource allocation and model modifications in a combined manner, where an initially suboptimal resource allocation can lead to better overall process executions. More specifically, the main contribution is twofold: (i) to present a proposal that leverages a variant of representation of processes as Refined Process Structure Trees (RPSTs) with a view to enabling novel resource allocation-driven task re-ordering and parallelisation in a principled manner, and (ii) to introduce a resource allocation paradigm that assigns tasks to resources taking into account the re-sequencing opportunities that can arise. The results show that we can yield improvements in a very high proportion of our experimental cases, while these improvements can reach 45% decrease in cycle time.

Key words

business process optimization, process models, resequencing, parallelism, resource allocation

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Publication information

Volume 20, Issue 4 (September 2023)
Year of Publication: 2023
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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Varvoutas, K., Kougka, G., Gounaris, A.: Systematic Exploitation of Parallel Task Execution in Business Processes. Computer Science and Information Systems, Vol. 20, No. 4. (2023),