Journal of Intelligent Manufacturing

, Volume 21, Issue 1, pp 65–73 | Cite as

A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty

  • Inés González-Rodríguez
  • Camino R. Vela
  • Jorge Puente
Article

Abstract

In this work we consider a multiobjective job shop problem with uncertain durations and crisp due dates. Ill-known durations are modelled as fuzzy numbers. We take a fuzzy goal programming approach to propose a generic multiobjective model based on lexicographical minimisation of expected values. To solve the resulting problem, we propose a genetic algorithm searching in the space of possibly active schedules. Experimental results are presented for several problem instances, solved by the GA according to the proposed model, considering three objectives: makespan, tardiness and idleness. The results illustrate the potential of the proposed multiobjective model and genetic algorithm.

Keywords

Job shop Scheduling Uncertain duration Multiobjective optimisation 

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Inés González-Rodríguez
    • 1
  • Camino R. Vela
    • 2
  • Jorge Puente
    • 2
  1. 1.Department of Mathematics, Statistics and ComputingUniversity of CantabriaSantanderSpain
  2. 2.A.I. Centre and Department of Computer ScienceUniversity of OviedoGijónSpain

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