A Study of Schedule Robustness for Job Shop with Uncertainty

Authors:
Inés González-Rodríguez;Jorge Puente;Ramiro Varela;Camino R. Vela
Affiliations:
Department of Mathematics, Statistics and Computing, University of Cantabria, Spain;A.I. Centre and Department of Computer Science, University of Oviedo, Spain;A.I. Centre and Department of Computer Science, University of Oviedo, Spain;A.I. Centre and Department of Computer Science, University of Oviedo, Spain
Venue:
IBERAMIA '08 Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence
Year:
2008

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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.