Discovering optimal resource allocations for what-if scenarios using data-driven simulation

IF 2.4 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Jorge Bejarano, Daniel Barón, Oscar González-Rojas, Manuel Camargo
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引用次数: 0

Abstract

Introduction 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. Methods 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. Results and discussion 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.
使用数据驱动的模拟发现假设场景的最佳资源分配
数据驱动的仿真允许从事件日志中发现流程仿真模型。生成的模型可用于模拟流程配置中的更改,并在执行流程之前评估流程的预期性能。目前,这些假设场景是由分析人员手动定义和评估的。除了为期望的性能寻找合适的场景的复杂性之外,现有的方法基于流和数据模式模拟场景,而不考虑基于资源的分析。资源对过程性能至关重要,因为它们影响成本、时间和质量。方法提出了一种自动发现最优资源分配的方法,以提高模拟情景的性能。我们描述了一个模型,将单个资源分配给它们适合的活动。然后,我们将介绍如何基于偏好和协作分配策略生成假设场景。基于用户自定义的多目标优化函数发现最优资源分配。结果和讨论该方法与模拟环境集成在一起,以比较更改分配策略时假设场景的性能权衡。对多个真实事件日志和合成事件日志的实验评估表明,优化资源分配可以提高仿真性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Computer Science
Frontiers in Computer Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.30
自引率
0.00%
发文量
152
审稿时长
13 weeks
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