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Systems 2016, 4(1), 15; doi:10.3390/systems4010015

Using Optimization Models for Scheduling in Enterprise Resource Planning Systems

OTH Regensburg, Innovation and Competence Centre for Production Logistics and Factory Planning, PO box 120327, Regensburg 93025, Germany
Academic Editor: Donald Kerr
Received: 12 December 2015 / Revised: 15 January 2016 / Accepted: 25 February 2016 / Published: 1 March 2016
(This article belongs to the Special Issue Enterprise Resource Planning Systems)
View Full-Text   |   Download PDF [1088 KB, uploaded 1 March 2016]   |  

Abstract

Companies often use specially-designed production systems and change them from time to time. They produce small batches in order to satisfy specific demands with the least tardiness. This imposes high demands on high-performance scheduling algorithms which can be rapidly adapted to changes in the production system. As a solution, this paper proposes a generic approach: solutions were obtained using a widely-used commercially-available tool for solving linear optimization models, which is available in an Enterprise Resource Planning System (in the SAP system for example) or can be connected to it. In a real-world application of a flow shop with special restrictions this approach is successfully used on a standard personal computer. Thus, the main implication is that optimal scheduling with a commercially-available tool, incorporated in an Enterprise Resource Planning System, may be the best approach. View Full-Text
Keywords: scheduling; optimization model; real world application; enterprise resource planning system; material requirements planning II; priority rules scheduling; optimization model; real world application; enterprise resource planning system; material requirements planning II; priority rules
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Herrmann, F. Using Optimization Models for Scheduling in Enterprise Resource Planning Systems. Systems 2016, 4, 15.

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