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Supporting Visual Exploration of Iterative Job Scheduling

Andrienko, G. ORCID: 0000-0002-8574-6295, Andrienko, N., Cordero Garcia, J. M. , Hecker, D. & Vouros, G. (2022). Supporting Visual Exploration of Iterative Job Scheduling. IEEE Computer Graphics and Applications, doi: 10.1109/MCG.2022.3163437

Abstract

We consider the general problem known as job shop scheduling, in which multiple jobs consist of sequential operations that need to be executed or served by appropriate machines having limited capacities. For example, train journeys (jobs) consist of moves and stops (operations) to be served by rail tracks and stations (machines). A schedule is an assignment of the job operations to machines and times where and when they will be executed. Developers of computational methods for job scheduling need tools enabling them to explore how their methods work. At a high level of generality, we define the system of pertinent exploration tasks and a combination of visualisations capable of supporting the tasks. We provide general descriptions of the purposes, contents, visual encoding, properties, and interactive facilities of the visualisations and illustrate them with images from an example implementation in air traffic management. We justify the design of the visualisations based on the tasks, principles of creating visualisations for pattern discovery, and scalability requirements. The outcomes of our research are sufficiently general to be of use in a variety of applications.

Publication Type: Article
Additional Information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Visualization, Schedules, Task analysis, Optimization, Job shop scheduling, Delays, Processor scheduling
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Departments: School of Science & Technology > Computer Science
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