A study of schedule robustness for job shop with uncertainty
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Springer
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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
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
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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
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All authors are supported by MEC-FEDER Grant TIN2007-67466-C02-01
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