Supporting Visual Exploration of Iterative Job Scheduling

Autor: Gennady Andrienko, Natalia Andrienko, Jose Manuel Cordero Garcia, Dirk Hecker, George A. Vouros
Přispěvatelé: Publica
Rok vydání: 2022
Předmět:
Zdroj: IEEE Computer Graphics and Applications
ISSN: 1558-1756
0272-1716
DOI: 10.1109/mcg.2022.3163437
Popis: 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. The 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 visualizations capable of supporting the tasks. We provide general descriptions of the purposes, contents, visual encoding, properties, and interactive facilities of the visualizations and illustrate them with images from an example implementation in air traffic management. We justify the design of the visualizations based on the tasks, principles of creating visualizations for pattern discovery, and scalability requirements. The outcomes of our research are sufficiently general to be of use in a variety of applications.
Databáze: OpenAIRE