Skip to main content
SpringerLink
Log in

Accessing feasible space in a generalized job shop scheduling problem with the fuzzy processing times: a fuzzy-neural approach

  • Special Issue Paper
  • Published:
Journal of the Operational Research Society

Abstract

This paper presents a fuzzy-neural approach for constraint satisfaction of a generalized job shop scheduling problem (GJSSP) fuzzy processing times. Our study is an extension of recently developed research in a GJSSP where the processing time of operations was constant. Our paper assumes that the processing time of jobs is uncertain. The proposed fuzzy-neural approach can be adaptively adjusted with weights of connections based on sequence resource and uncertain processing time constraints of the GJSSP during its processing. The computational results show that the proposed neural approach is able to find good solutions in reasonable time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 7
Figure 3
Figure 4
Figure 5
Figure 6
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16

References

  • Cheng R, Gen M and Tozawa T (1995). Vehicle routing problem with fuzzy due-time using genetic algorithms. J Japan Soc Fuzzy Syst 7: 1050–1061.

    Google Scholar 

  • Foo S-Y and Takefuji Y (1988a). Neural networks for solving job-shop scheduling: Job 1. Problem representation. Proceedings of the IEEE IJCNN, Vol. II. IEEE: pp. 275–282.

  • Foo S-Y and Takefuji Y (1988b). Stochastic neural networks for solving job-shop scheduling: Job 2. Architecture and simulations. Proceedings of the IEEE IJCNN, Vol. II. IEEE: pp. 283–290.

  • Foo S-Y, Takefuji Y and Szu H (1994). Job-shop scheduling based on modified Tank-Hopfield linear programming networks. Eng Appl Artif Intel 7: 321–327.

    Article  Google Scholar 

  • Fortemps P (1997). Job shop scheduling with imprecise durations: a fuzzy approach. IEEE Trans Fuzzy Syst 5: 557–569.

    Article  Google Scholar 

  • Fox MS and Zweben M (1993). Knowledge-Based Scheduling. Morgan Kaufmann: San Manteo, CA.

    Google Scholar 

  • Haibin Y, Haobo W, Xinhe X and Jinsong X (1997). A neural-based approach to production scheduling. Proceedings of the 1997 American Control Conference. Vol. 2. The American Automatic Control Council: Albuquerque, New Mexico, pp. 1012–1027.

    Google Scholar 

  • Han S, Ishii H and Fujii S (1992). One machine scheduling problem with fuzzy due dates. Eur J Opl Res 79: 1–12.

    Article  Google Scholar 

  • Hopfield JJ and Tank DW (1985). Neural computation of decisions in optimization problems. Biol Cybern 52: 141–152.

    Google Scholar 

  • Ishibuchi H, Murata T and Lee K-H (1996). Formulation of fuzzy flow shop scheduling problems with fuzzy processing time. Proceedings of 5th IEEE International Conference on Fuzzy Systems. The IEEE Neural Networks Council: New Orleans, USA, pp. 199–205.

    Book  Google Scholar 

  • Ishibuchi H, Yamamoto N, Murata T and Tanaka H (1994). Genetic algorithms and neighborhood search algorithms for fuzzy flow shop scheduling problems. Fuzzy Sets and Syst 67: 81–100.

    Article  Google Scholar 

  • Ishii H and Tada M (1995). Single machine scheduling problem with fuzzy precedence relation. Eur J Opl Res 87: 284–288.

    Article  Google Scholar 

  • Ishii H, Tada M and Masuda T (1992). Two scheduling problems with fuzzy due-dates. Fuzzy Sets Syst 46: 339–347.

    Article  Google Scholar 

  • McCahon CS and Lee ES (1992). Fuzzy job sequencing for a flow shop. Eur J Opl Res 62: 294–301.

    Article  Google Scholar 

  • Murata T and Ishibuchi H (1997). Reformulation of various non-fuzzy scheduling problems using the concept of fuzzy due-date. Proceedings of the 6th IEEE International Conference on Fuzzy Systems. The IEEE Neural Networks Council: Barcelona, Spain, pp. 447–452.

    Chapter  Google Scholar 

  • Tsujimura Y, Gen M and Kubota E (1995). Solving job-shop scheduling problem with fuzzy processing time using genetic algorithm. J Japan Soc Fuzzy Syst 7: 1073–1083.

    Google Scholar 

  • Van Hentenryck P (1989). Constraint Satisfaction and Logic Programming. MIT Press: Cambridge, MA.

    Google Scholar 

  • Wets RJ-B (1974). Stochastic programming with fixed recourse: the equivalent deterministic program. SIAM Rev 16: 309–339.

    Article  Google Scholar 

  • Willems TM and Brandts LEMW (1995). Implementing heuristics as an optimization criterion in neural networks for job-shop scheduling. J Intell Manuf 6: 377–387.

    Article  Google Scholar 

  • Willems TM and Rooda JE (1994). Neural networks for job-shop scheduling. Contr Eng Pract 2: 31–39.

    Article  Google Scholar 

  • Wilson GV and Pawley GS (1988). On the stability of the travelling salesman problem algorithm of Hopfield and Tank. Biol Cybern 58: 63–70.

    Article  Google Scholar 

  • Xie Y, Xie JY and Li J (2005). Fuzzy due dates job shop scheduling problem based on neural network. Lect Notes Comput Sci 3496: 782–787.

    Article  Google Scholar 

  • Yang S and Wang D (2000). Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling. IEEE Trans Neural Networks 11: 474–486.

    Article  Google Scholar 

  • Zhang CS and Yan PF (1995). Neural network method of solving job-shop scheduling problem. ACTA Automat Sin 21: 706–712.

    Google Scholar 

  • Zhou DN, Charkassky V, Baldwin TR and Olson DE (1991). A neural network approach to job-shop scheduling. IEEE Trans Neural Networks 2: 175–179.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Tehran, Tehran, Iran

    R Tavakkoli-Moghaddam

  2. Iran University of Science and Technology, Tehran, Iran

    N Safaei

  3. Abti-American University of Nigeria, Yola, Nigeria and American University, Washington, DC, USA

    M M O Kah

Authors
  1. R Tavakkoli-Moghaddam
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N Safaei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M M O Kah
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to R Tavakkoli-Moghaddam.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tavakkoli-Moghaddam, R., Safaei, N. & Kah, M. Accessing feasible space in a generalized job shop scheduling problem with the fuzzy processing times: a fuzzy-neural approach. J Oper Res Soc 59, 431–442 (2008). https://doi.org/10.1057/palgrave.jors.2602351

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/palgrave.jors.2602351

Keywords

Search

Navigation