Solving the Problem of Flow Shop Scheduling by Neural Network Approach

  • Saeed Rouhani
  • Mohammad Fathian
  • Mostafa Jafari
  • Peyman Akhavan
Part of the Communications in Computer and Information Science book series (CCIS, volume 88)


If there is a continuous flow of production jobs for some machines, the problem of flow shop scheduling arises. As mentioned in many researches, the complexities of this problem are of exponential kind; therefore it is necessary to design less complex methods or algorithms for solving it. In this paper, a new solution is presented for this kind of scheduling problem by using the idea of neural networks. In fact, this research is a response to the need for solving large and complex problems of this type by non-classical methods. The purpose of the paper is to create an artificial intelligence for doing this kind of scheduling via the neural network training process. Here, the neural network has been trained by using training data obtained from optimal sequence of solved problems of flow shop scheduling. The trained network can provide a priority which shows the sequence of the job and will be very close to the optimal sequence.


Artificial Intelligence Neural Networks Scheduling Flow shop problem 


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  1. 1.
    Ashour, S.: Sequencing Theory. Springer, Berlin (1972)zbMATHGoogle Scholar
  2. 2.
    Brown, A.P.G., Lomnicki, Z.A.: Some applications of the branch and bound algorithm to the machine scheduling problem. Operational Research Quarterly 17, 173–186 (1966)CrossRefGoogle Scholar
  3. 3.
    Brucker, P.: Scheduling Algorithms. Springer, Berlin (1998)zbMATHGoogle Scholar
  4. 4.
    Conway, R.L., Maxwell, W.L., Miller, L.W.: Theory of Scheduling. Addison Wesley, Reading (1967)zbMATHGoogle Scholar
  5. 5.
    Dempster, M.A.H., Lenstra, J.K., Rinnooy Kan, A.H.G. (eds.): Deterministic and Stochastic Scheduling. Reidel, Dordrecht (1982)zbMATHGoogle Scholar
  6. 6.
    Akyol, D.E.: Application of neural networks to heuristic scheduling algorithms. Computers & Industrial Engineering 46, 679–696 (2004)CrossRefGoogle Scholar
  7. 7.
    El-Bouri, A., Balakrishnan, S., Popplewell, N.: Jobs on a single machine: A neural network approach. European Journal of Operational Research 126, 474–490 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    El-Bouri, A., Balakrishnan, S., Popplewell, N.: A neural network to enhance local search in the permutation flowshop. Computers & Industrial Engineering 49, 182–196 (2005)CrossRefGoogle Scholar
  9. 9.
    Framinan, J.M., Gupta, J.N.D., Leisten, R.: A review and classification of heuristics for permutation flow-shop scheduling with makespan objective. Journal of the Operational Research Society 55, 1243–1255 (2004)zbMATHCrossRefGoogle Scholar
  10. 10.
    Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-completeness. W.H. Freeman and Company, San Francisco (1979)zbMATHGoogle Scholar
  11. 11.
    Geismar, H.N., Dawande, M., Sriskandarajah, C.: Robotic cells with parallel machines: Throughput maximization in constant travel-time cells. Journal of Scheduling 7, 375–395 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Gupta, J.N.D.: Heuristic algorithms for multistage flowshop scheduling problem. AIIE Transactions 4, 11–18 (1972)Google Scholar
  13. 13.
    Gupta, J.N.D.: A review of flowshop scheduling research. In: Ritzman, L.P., Krajewski, L.J., Berry, W.L., Goodman, S.T., Hardy, S.T., Vitt, L.D. (eds.) Disaggregation Problems in Manufacturing and Service Organizations. Martinus Nijhoff, The Hague, pp. 363–388 (1979)Google Scholar
  14. 14.
    Ignall, E., Schrage, L.: Application of branch-and-bound technique to some flow shop problems. Operations Research 13, 400–412 (1965)CrossRefMathSciNetGoogle Scholar
  15. 15.
    Gupta, J.N.D., Stafford Jr., E.F.: Flowshop scheduling research after five decades. European Journal of Operational Research 169, 699–711 (2006)zbMATHCrossRefGoogle Scholar
  16. 16.
    Johnson, S.M.: Optimal two- and three-stage production schedules with setup times included. Naval Research logistics Quarterly 1, 61–68 (1954)CrossRefGoogle Scholar
  17. 17.
    Lomnicki, Z.A.: A branch and bound algorithm for the exact solution of the three machine scheduling problem. Operational Research Quarterly 16, 89–100 (1965)CrossRefGoogle Scholar
  18. 18.
    McMahon, G.B., Burton, P.G.: Flowshop scheduling with the branch and bound method. Operations Research 15, 473–481 (1967)CrossRefGoogle Scholar
  19. 19.
    Morton, T.E., Pentico, D.W.: Heuristic Scheduling Systems. Wiley, New York (1993)Google Scholar
  20. 20.
    Osman, I.H., Kelly, J.P.: Meta-heuristics: Theory and Applications. Kluwer Academic Publishers, Boston (1996)zbMATHGoogle Scholar
  21. 21.
    Potts, C.N., Kovalyov, M.Y.: Scheduling with batching: A review. European Journal of Operational Research 120, 228–249 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  22. 22.
    Ruiz, R., Maroto, C., Alcaraz, J.: Solving the flowshop scheduling problem with sequence dependent setup times using advanced metaheuristics. European Journal of Operational Research 165, 34–54 (2005)zbMATHCrossRefMathSciNetGoogle Scholar
  23. 23.
    Sabuncuoglu, I., Gurgun, B.: A neural network model for scheduling problems. European Journal of Operational Research 93, 288–299 (1996)zbMATHCrossRefGoogle Scholar
  24. 24.
    Tanaev, V.S., Sotskov, Y.N., Strusevich, V.A.: Scheduling Theory: Multi-stage Systems. Kluwer Academic Publishers, Dordrecht (1994)zbMATHGoogle Scholar
  25. 25.
    Wagner, H.M.: An integer linear-programming model for machine scheduling. Naval Research Logistics Quarterly 6, 131–140 (1959)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Saeed Rouhani
    • 1
  • Mohammad Fathian
    • 2
  • Mostafa Jafari
    • 2
  • Peyman Akhavan
    • 2
  1. 1.Department of Industrial Engineering, Firoozkoh BranchIslamic Azad UniversityFiroozkohIran
  2. 2.Department of Industrial EngineeringIran University of Science and TechnologyTehranIran

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