Solving production scheduling problems using advanced model checking tools

Panopoulos, D; Metaxiotis, K

dc.contributor.author	Panopoulos, D	en
dc.contributor.author	Metaxiotis, K	en
dc.date.accessioned	2014-03-01T01:25:10Z
dc.date.available	2014-03-01T01:25:10Z
dc.date.issued	2006	en
dc.identifier.issn	09528091	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17577
dc.subject	Job-shop	en
dc.subject	Model checking	en
dc.subject	Production scheduling	en
dc.subject	Timed automata	en
dc.subject.other	Algorithms	en
dc.subject.other	Job analysis	en
dc.subject.other	Large scale systems	en
dc.subject.other	Mathematical models	en
dc.subject.other	Polynomials	en
dc.subject.other	Problem solving	en
dc.subject.other	Model checking tools	en
dc.subject.other	Production scheduling	en
dc.subject.other	Timed automata	en
dc.subject.other	Production engineering	en
dc.title	Solving production scheduling problems using advanced model checking tools	en
heal.type	journalArticle	en
heal.identifier.primary	10.1504/IJCAT.2006.010079	en
heal.identifier.secondary	http://dx.doi.org/10.1504/IJCAT.2006.010079	en
heal.publicationDate	2006	en
heal.abstract	The main scope of this paper is the implementation of a method for production scheduling, using advanced model checking tools. This method makes use of timed automata to model complex production scheduling problems such as the job-shop and the open-shop scheduling problems. By modelling scheduling problems using timed automata, feasible schedules correspond to paths in the automata, while finding the optimum schedule corresponds to finding the shortest path in an automaton. Several algorithms and heuristics have been proposed for finding the shortest paths in timed automata, which are mainly based on the implementation of graph algorithms that search the transition graph. In our work, an advanced model design and checking tool, called UPPAAL, has been used to implement and test the above method on a number of different models and to show the effectiveness of such an approach in terms of finding optimal or near to optimal, schedules in polynomial time, even for large-scale problems. Copyright © 2006 Inderscience Enterprises Ltd.	en
heal.journalName	International Journal of Computer Applications in Technology	en
dc.identifier.doi	10.1504/IJCAT.2006.010079	en
dc.identifier.volume	26	en
dc.identifier.issue	1-2	en
dc.identifier.spage	37	en
dc.identifier.epage	48	en