2020/04/20 by Bedilia Estrada-Torres, Manuél Camargo, Estrada-Torres, Bedilia +5
Business, Management and Accounting · Decision Sciences · #Business Process Modeling and Analysis #FOS: Computer and information sciences #Simulation Techniques and Applications #Software Engineering (cs.SE)
paper · pdf · doi:10.48550/arxiv.2004.09138
openalex publication_date 2020/04/20 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
Business process simulation is a versatile technique for analyzing business\nprocesses from a quantitative perspective. A well-known limitation of process\nsimulation is that the accuracy of the simulation results is limited by the\nfaithfulness of the process model and simulation parameters given as input to\nthe simulator. To tackle this limitation, several authors have proposed to\ndiscover simulation models from process execution logs so that the resulting\nsimulation models more closely match reality. Existing techniques in this field\nassume that each resource in the process performs one task at a time. In\nreality, however, resources may engage in multitasking behavior. Traditional\nsimulation approaches do not handle multitasking. Instead, they rely on a\nresource allocation approach wherein a task instance is only assigned to a\nresource when the resource is free. This inability to handle multitasking leads\nto an overestimation of execution times. This paper proposes an approach to\ndiscover multitasking in business process execution logs and to generate a\nsimulation model that takes into account the discovered multitasking behavior.\nThe key idea is to adjust the processing times of tasks in such a way that\nexecuting the multitasked tasks sequentially with the adjusted times is\nequivalent to executing them concurrently with the original processing times.\nThe proposed approach is evaluated using a real-life dataset and synthetic\ndatasets with different levels of multitasking. The results show that, in the\npresence of multitasking, the approach improves the accuracy of simulation\nmodels discovered from execution logs.\n