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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.
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.
| Original language | English |
|---|---|
| Title of host publication | 20th International Conference on Distributed Computing and Artificial Intelligence |
| Subtitle of host publication | Special Sessions |
| Number of pages | 10 |
| Volume | 741 |
| ISBN (Electronic) | 978-3-031-38318-2 |
| DOIs | |
| Publication status | Published - 26 Jul 2023 |
| Event | International Conference on Distributed Computing and Artificial Intelligence - Guimarães, Portugal Duration: 12 Jul 2023 → 14 Jul 2023 https://www.dcai-conference.net/ |
Publication series
| Name | Lecture Notes in Networks and Systems |
|---|---|
| Publisher | Springer |
| ISSN (Print) | 2367-3370 |
| ISSN (Electronic) | 2367-3389 |
Conference
| Conference | International Conference on Distributed Computing and Artificial Intelligence |
|---|---|
| Abbreviated title | DCAI |
| Country/Territory | Portugal |
| City | Guimarães |
| Period | 12/07/23 → 14/07/23 |
| Internet address |
Research Field
- High-Performance Vision Systems
- Outside the AIT Research Fields
Keywords
- job scheduling
- probability
- web application
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Dive into the research topics of 'Web based application for probability job scheduling'. Together they form a unique fingerprint.Activities
- 1 Participation in Conference Committees
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20th International Conference on Distributed Computing and Artificial Intelligence (DCAI 2023) (Event)
Michno, T. (Reviewer)
2023 → …Activity: Editorial and Review Activities › Participation in Conference Committees