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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/31969

Title: A study of schedule robustness for job shop with uncertainty
Author(s): González Rodríguez, Inés
Puente Peinador, Jorge
Varela Arias, José Ramiro
Rodríguez Vela, María del Camino
Issue date: 2008
Publisher: Springer
Publisher version: http://dx.doi.org/10.1007/978-3-540-88309-8_4
Format extent: p. 31-41
Abstract: We consider a job shop problem with uncertain processing times modelled as triangular fuzzy numbers and propose a methodology to study solution robustness with respect to different perturbations in the durations. This methodology is applied to obtain experimental results for several problem instances, using a hybrid genetic algorithm that minimises the expected makespan. We conclude that taking into account the uncertainty information provided by fuzzy numbers produces proactive solutions, coping well with posterior changes in processing times
Description: 11th Ibero-American Conference on AI, Lisbon, Portugal
La publicación final está disponible en Springer vía http://dx.doi.org/10.1007/978-3-540-88309-8_4
URI: http://hdl.handle.net/10651/31969
ISBN: 978-3-540-88308-1
Sponsored: All authors are supported by MEC-FEDER Grant TIN2007-67466-C02-01
Project id.: MEC-FEDER/TIN2007-67466-C02-01
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