Abstract
The problem of job scheduling has been studied by various researchers since the early fifties of the 20th century. It can be defined as finding the most optimal assignment of different jobs to some resources such as machines, e.g. to find the lowest cost, which may be time. One of the most common problems in preparing the job scheduling is the precise definition of the time required to complete the task. In some situations this can be difficult because there may be many factors with uncertainties. In this paper we have focused on this problem from a practical point of view, which may be useful for e.g. project managers. For such situation, solutions using fuzzy sets or probability distributions may be relevant, but unfortunately they may be not easy to understand and use by people without advanced mathematical background. This paper presents a tool for probabilistic job scheduling. The web-based application has been prepared as well as a job scheduling approach using probability and four types of results showing the most probable total time, least probable, maximum and minimum. This can be useful for decision making by e.g. project managers. As a result, a web application for probabilistic job scheduling was created using Python, HTML, CSS and Flask framework.
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Michno, T., Deniziak, R.S., Michno, A. (2023). Web Based Application for Probability Job Scheduling. In: Mehmood, R., et al. Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. DCAI 2023. Lecture Notes in Networks and Systems, vol 741. Springer, Cham. https://doi.org/10.1007/978-3-031-38318-2_4
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