An Evolutionary Approach to Designing and Solving Fuzzy Job-Shop Problems

  • Inés González-Rodríguez
  • Camino R. Vela
  • Jorge Puente
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3562)


In the sequel we shall consider the fuzzy job-shop problem, a variation of the job-shop problem where the duration of tasks may be uncertain and where due-date constraints are flexible. Our aim is to provide a semantics for this problem and fix some criteria to analyse solutions obtained by Evolutionary Algorithms.


Schedule Problem Completion Time Fuzzy Number Satisfaction Degree Fuzzy Processing Time 
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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  1. 1.
    Brucker, P.: Scheduling Algorithms, 4th edn. Springer, Heidelberg (2004)zbMATHGoogle Scholar
  2. 2.
    Dubois, D., Fargier, H., Fortemps, P.: Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge. European Journal of Operational Research 147, 231–252 (2003)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Mattfeld, D.C.: Evolutionary Search and the Job Shop Investigations on Genetic Algorithms for Production Scheduling. Springer, Heidelberg (1995)Google Scholar
  4. 4.
    Bortolan, G., Degani, R.: A review of some methods for ranking fuzzy subsets. In: Dubois, D., Prade, H., Yager, R. (eds.) Readings in Fuzzy Sets for Intelligence Systems, pp. 149–158. Morgan Kaufmann, Amsterdam (1993)Google Scholar
  5. 5.
    Sakawa, M., Kubota, R.: Fuzzy programming for multiobjective job shop scheduling with fuzzy processing time and fuzzy duedate through genetic algorithms. European Journal of Operational Research 120, 393–407 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Bellman, R.E., Zadeh, L.A.: Decision-making in a fuzzy environment. Management Science 17, 141–164 (1970)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Giffler, B., Thomson, G.L.: Algorithms for solving production scheduling problems. Operations Research 8, 487–503 (1960)zbMATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Varela, R., Vela, C.R., Puente, J., Gómez, A.: A knowledge-based evolutionary strategy for scheduling problems with bottlenecks. European Journal of Operational Research 145, 57–71 (2003)zbMATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Chanas, S., Kasperski, A.: Possible and necessary optimality of solutions in the single machine scheduling problem with fuzzy parameters. Fuzzy Sets and Systems 142, 359–371 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Brucker, P., Jurisch, B., Sievers, B.: Code of a branch & bound algorithm for the job shop problem (1994),

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Inés González-Rodríguez
    • 1
  • Camino R. Vela
    • 1
  • Jorge Puente
    • 1
  1. 1.Dept. of Computer ScienceUniversity of OviedoSpain

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