{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T00:00:11Z","timestamp":1781654411817,"version":"3.54.5"},"reference-count":23,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T00:00:00Z","timestamp":1698883200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Comput. Sci."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>Data-driven simulation allows the discovery of process simulation models from event logs. The generated model can be used to simulate changes in the process configuration and to evaluate the expected performance of the processes before they are executed. Currently, these what-if scenarios are defined and assessed manually by the analysts. Besides the complexity of finding a suitable scenario for a desired performance, existing approaches simulate scenarios based on flow and data patterns leaving aside a resource-based analysis. Resources are critical on the process performance since they carry out costs, time, and quality.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This paper proposes a method to automate the discovery of optimal resource allocations to improve the performance of simulated what-if scenarios. We describe a model for individual resource allocation only to activities they fit. Then, we present how what-if scenarios are generated based on preference and collaboration allocation policies. The optimal resource allocations are discovered based on a user-defined multi-objective optimization function.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results and discussion<\/jats:title><jats:p>This method is integrated with a simulation environment to compare the trade-off in the performance of what-if scenarios when changing allocation policies. An experimental evaluation of multiple real-life and synthetic event logs shows that optimal resource allocations improve the simulation performance.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fcomp.2023.1279800","type":"journal-article","created":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T06:18:30Z","timestamp":1698992310000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Discovering optimal resource allocations for what-if scenarios using data-driven simulation"],"prefix":"10.3389","volume":"5","author":[{"given":"Jorge","family":"Bejarano","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Bar\u00f3n","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oscar","family":"Gonz\u00e1lez-Rojas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manuel","family":"Camargo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,11,2]]},"reference":[{"key":"B1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/ICDM.2017.9","article-title":"\u201cSplit miner: Discovering accurate and simple business process models from event logs,\u201d","volume-title":"IEEE International Conference on Data Mining (ICDM)","author":"Augusto","year":"2017"},{"key":"B2","first-page":"40","article-title":"\u201cA BPMN extension to enable the explicit modeling of task resources,\u201d","volume-title":"CEUR Workshop Proceedings","author":"Bocciarelli","year":"2016"},{"key":"B3","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1007\/978-3-642-25535-9_32","article-title":"\u201cDefining and analyzing resource assignments in business processes with RAL,\u201d","volume-title":"Service-Oriented Computing","author":"Cabanillas","year":"2011"},{"key":"B4","doi-asserted-by":"publisher","first-page":"113284","DOI":"10.1016\/j.dss.2020.113284","article-title":"Automated discovery of business process simulation models from event logs","volume":"134","author":"Camargo","year":"2020","journal-title":"Decis. 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