Skip to main content

A hybrid heuristic approach for production planning in supply chain networks

Abstract

Planning distributed manufacturing facilities is one of the most challenging tasks in the supply chain management. This paper proposes a production planning algorithm for the multi-level, multi-item capacitated lot-sizing problem (MLCLSP) in a supply chain network that takes back order into account. MLCLSP is a mixed integer linear programming (MIP) problem and is NP-hard. This paper presents an efficient, hybrid, heuristic algorithm named greedy rolling horizon search (GRHS) that combines a rolling horizon local search heuristic with an exact linear program (LP) solver. Computational experiments show that GRHS performs well in terms of total costs and computational time and is superior to existing meta-heuristics, such as tabu search, simulated annealing, and genetic algorithms.

This is a preview of subscription content, access via your institution.

References

  1. Akartunali K, Miller AJ (2009) A heuristic approach for big bucket multi-level production planning problems. Eur J Oper Res 193:396–411

    Article  MATH  MathSciNet  Google Scholar 

  2. Almada-Lobo B, James RJW (2010) Neighbourhood search meta-heuristics for capacitated lot-sizing with sequence-dependent setups. Int J Prod Res 48:861–878

    Article  MATH  Google Scholar 

  3. Almeder C (2010) A hybrid optimization approach for multi-level capacitated lot-sizing problems. Eur J Oper Res 200:599–606

    Article  MATH  Google Scholar 

  4. Belvaux G, Wolsey LA (2001) Modeling practical lot-sizing problems as mixed-integer programs. Manag Sci 47:993–1007

    Article  MATH  Google Scholar 

  5. Chan FTS, Chung SH (2004) A multi-criterion genetic algorithm for order distribution in a demand driven supply chain. Int J Comput Integr Manuf 17(4):339–351

    Article  Google Scholar 

  6. Chan FTS, Tibrewal RK, Prakash A, Tiwari MK (2014) A biased random key genetic algorithm approach for inventory-based multi-item lot-sizing problem. J Eng Manuf. doi:10.1177/0954405414523594

    Google Scholar 

  7. Danna E, Rothberg E, Pape CE (2005) Exploring relaxation induced neighborhoods to improve MIP solutions. Math Program 102:71–90

    Article  MATH  MathSciNet  Google Scholar 

  8. Ertogral K, Wu SD (2000) Auction-theoretic coordination of production planning in the supply chain. IIE Trans 32:931–940

    Google Scholar 

  9. Federgruen A, Meissner J, Michal T (2007) Progressive interval heuristics for multi-item capacitated lot-sizing problems. Oper Res 55:490–502

    Article  MATH  MathSciNet  Google Scholar 

  10. Fischetti M, Lodi A (2008) Repairing MIP infeasibility through local branching. Comput Oper Res 35:1436–1445

    Article  MATH  MathSciNet  Google Scholar 

  11. Glover F (1989) Tabu search—part I. ORSA J Comput 1:190–206

    Article  MATH  MathSciNet  Google Scholar 

  12. Glover F (1990) Tabu search—part II. ORSA J Comput 2:4–32

    Article  MATH  Google Scholar 

  13. Goren HG, Tunali S, Jans R (2012) A hybrid approach for the capacitated lot sizing problem with setup carryover. Int J Prod Res 50:1582–1597

    Article  Google Scholar 

  14. Helber S, Sahling F (2010) A fix-and-optimize approach for the multi-level capacitated lot sizing problem. Int J Prod Econ 123:247–256

    Article  Google Scholar 

  15. Hung YF, Chien KL (2000) A multi-class multi-level capacitated lot sizing model. J Oper Res Soc 51:1309–1318

    Article  MATH  Google Scholar 

  16. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671–680

    Article  MATH  MathSciNet  Google Scholar 

  17. Li Y, Tao Y, Wang F (2012) An effective approach to multi-item capacitated dynamic lot-sizing problems. Int J Prod Res 50:5348–5362

    Article  Google Scholar 

  18. Maes J, McClain JO, Van Wassenhove LN (1991) Muti-level capacitated lotsizing complexity and LP-based heuristics. Eur J Oper Res 53:131–148

    Article  MATH  Google Scholar 

  19. Sahling F, Buschkuhl L, Tempelmeier H, Helber S (2009) Solving a multi-level capacitated lot sizing problem with multi-period setup carry-over via a fix-and-optimize heuristic. Comput Oper Res 36:2546–2553

    Article  MATH  Google Scholar 

  20. Stadtler H (2003) Multilevel lot sizing with setup times and multiple constrained resources: internally rolling schedules with lot-sizing windows. Oper Res 51:487–502

    Article  MATH  Google Scholar 

  21. Vergana FE, Khouja M, Michalewicz Z (2002) An evolutionary algorithm for optimizing material flow in supply chain. Comput Ind Eng 43:407–421

    Article  Google Scholar 

  22. Wu T, Shi L (2011) Mathematical models for capacitated multi-level production planning problems with linked lot sizes. Int J Prod Res 49:6227–6247

    Article  Google Scholar 

  23. Wu CH, Lin JT, Wu HH (2010) Robust production and transportation planning in thin film transistor-liquid crystal display (TFT-LCD) industry under demand and price uncertainties. Int J Prod Res 48:6037–6060

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hyun Joon Shin.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kim, D., Shin, H.J. A hybrid heuristic approach for production planning in supply chain networks. Int J Adv Manuf Technol 78, 395–406 (2015). https://doi.org/10.1007/s00170-014-6599-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-014-6599-4

Keywords

  • Supply chain planning
  • Multi-level multi-item
  • Capacitated lot sizing
  • Back order
  • Hybrid heuristic
  • Meta-heuristics