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A Study of Schedule Robustness for Job Shop with Uncertainty

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 5290)

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.

Keywords

  • Fuzzy Number
  • Hybrid Genetic Algorithm
  • Possibility Distribution
  • Task Duration
  • Critical Block

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-540-88309-8_4
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© 2008 Springer-Verlag Berlin Heidelberg

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González-Rodríguez, I., Puente, J., Varela, R., Vela, C.R. (2008). A Study of Schedule Robustness for Job Shop with Uncertainty. In: Geffner, H., Prada, R., Machado Alexandre, I., David, N. (eds) Advances in Artificial Intelligence – IBERAMIA 2008. IBERAMIA 2008. Lecture Notes in Computer Science(), vol 5290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88309-8_4

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  • DOI: https://doi.org/10.1007/978-3-540-88309-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88308-1

  • Online ISBN: 978-3-540-88309-8

  • eBook Packages: Computer ScienceComputer Science (R0)