Author:
Almeida Ana, ,Marreiros Goreti
Abstract
The model we present supporting collaborative scheduling in complex dynamic manufacturing environments, considers the interaction between an agent-based scheduling module (ASM) and a group decision support module (GDSM). The ASM outputs a set of candidate scheduling solutions, each generated based on specific criteria and/or by a particular method. Scheduling is a multicriteria decision problem in practice where different schedulers may agree on key objectives but differ greatly on their relative importance in any given situation. Interaction among scheduling actors is supported by the GDSM selecting a scheduling solution.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Reference27 articles.
1. K. R. Baker, “Introduction to Sequencing and Scheduling,” John Wiley & Sons, (New York, USA), 1974.
2. E. L. Lawler, J. K. Lenstra, A. H. G. Rinnooy Kan, and D. B. Shmoys, “Sequencing and scheduling: algorithms and complexity,” in Handbooks Operations Research and Management Science, Vol.4, 1993.
3. J. Marinho, “SCALINTEL: A DSS Prototype with Scalable Intelligence,” Proceedings of the 1st International Conference On Knowledge Engineering and Decision Support (CKEDS’04), 2004.
4. R. Kowalczyk, V. Phiong, S. Dunstall, and B. Owens, “Towards supporting collaborative scheduling in adaptive supply networks with negotiation agents,” Proc. Theory and Applications of e-Negotiations, Poznan, Poland, 2004.
5. K. N. McKay, F. R. Safayeni, and J. A. Buzacott, “Job-Shop Scheduling Theory: What is relevant?,” Interfaces, Vol.18, pp. 84-90, 1988.
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