Skip to main content

Advertisement

Log in

Heuristic search algorithms for lot streaming in a two-machine flowshop

  • Original Article
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The objective of this paper is to propose and evaluate heuristic search algorithms for a two-machine flowshop problem with multiple jobs requiring lot streaming that minimizes makespan. A job here implies many identical items. Lot streaming creates sublots to move the completed portion of a production lot to second machine. The three heuristic search algorithms evaluated in this paper are Baker’s approach (Baker), genetic algorithm (GA) and simulated annealing (SA) algorithm. To create neighborhoods for SA, three perturbation schemes, viz., pair-wise exchange, insertion and random insertion are used, and the performance of these on the final schedule is also compared. A wide variety of data sets is randomly generated for comparative evaluation. The parameters for GA and SA are obtained after conducting sensitivity analysis. The genetic algorithm is found to perform well for lot streaming in the two-machine flowshop scheduling.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Baker KR (1974) Introduction to sequencing and scheduling. Wiley, New York

  2. Pinedo M, Chao X (1997) Operations scheduling. McGraw-Hill, New York

  3. Sule DR (1997) Industrial scheduling. PWS, Boston

  4. Potts CN, Wassenhove LN (1992) Integrating scheduling with batching and lot-sizing. J Oper Res Soc 43(5):395–406

    MATH  Google Scholar 

  5. Potts CN, Baker KR (1989) Flowshop scheduling with lot streaming. Oper Res Lett 8:297–303

    Article  MATH  MathSciNet  Google Scholar 

  6. Baker KR (1995) Lot streaming in the two-machine flow shop with setup times. Ann Oper Res 57:1–11

    Article  MATH  Google Scholar 

  7. Glass CA, Gupta JND, Potts CN (1994) Lot streaming in three-stage process. Eur J Oper Res 75:378–394

    MATH  Google Scholar 

  8. Vickson RG (1995) Optimal lot streaming for multiple products in a two-machine flowshop, Eur J Oper Res 85:556–575

    Google Scholar 

  9. Sriskandarajah C, Wagneur E (1999) Lot streaming and scheduling multiple products in two-machine no-wait flowshops. IIE Trans 31:695–707

    Article  Google Scholar 

  10. Kumar S, Bagchi TP, Sriskandarajah C (2000) Lot streaming and scheduling heuristics for m-machine no-wait flowshops. Comput Ind Eng 38:149-172

    Article  Google Scholar 

  11. Johnson SM (1959) Sequencing n jobs on two machines with arbitrary time lags. Manage Sci 5:293–303

    Article  Google Scholar 

  12. Goldberg DE (2000) Genetic algorithms in search, optimization and machine leaning. Addison-Wesley, Boston

  13. Murata T, Ishibuchi H, Tanaka H (1996) Genetic algorithms for flowshop scheduling problems. Comput Ind Eng 30(4)1061–1071

    Google Scholar 

  14. van Laarhovan PJM, Aarts EHL (1987) Simulated annealing: theory and applications. Kluwer, Dordrecht

    Google Scholar 

  15. Ogbu FA, Smith DK (1990) The application of the simulated annealing algorithm to the solution of the n/m/C max flowshop problem. Comput Oper Res 17:243–253

    Article  MATH  MathSciNet  Google Scholar 

  16. Parthasarathy S, Rajendran C (1997) An experimental evaluation of heuristics for scheduling in a real-life flowshop with sequence-dependent setup time of jobs. Int J Prod Econ 49:255–263

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S.G. Ponnambalam.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Marimuthu, S., Ponnambalam, S. Heuristic search algorithms for lot streaming in a two-machine flowshop. Int J Adv Manuf Technol 27, 174–180 (2005). https://doi.org/10.1007/s00170-004-2127-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-004-2127-2

Keywords

Navigation