Skip to main content
SpringerLink
Log in

Uncertain aggregate production planning

  • Focus
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Based on uncertainty theory, multiproduct aggregate production planning model is presented, where the market demand, production cost, subcontracting cost, etc., are all characterized as uncertain variables. The objective is to maximize the belief degree of obtaining the profit more than the predetermined profit over the whole planning horizon. When these uncertain variables are linear, the objective function and constraints can be converted into crisp equivalents, the model is a nonlinear programming, then can be solved by traditional methods. An example is given to illustrate the model and the converting method.

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

Similar content being viewed by others

References

  • Baykasoglu A, Gocken T (2010) Multi-objective aggregate production planning with fuzzy parameters. Adv Eng Softw 41(9):1124–1131

    Article  MATH  Google Scholar 

  • Bergstrom G, Smith B (1970) Multi-item production planning-an extension of the HMMS rules. Manag Sci 16(10):614–629

    Article  Google Scholar 

  • Bitran G, and Yanassee H (1984) Deterministic approximations to stochastic production problems. Oper Res 32(5):999–1018

    Article  MathSciNet  MATH  Google Scholar 

  • Fung R, Tang J, Wang D (2003) Multiproduct aggregate production planning with fuzzy demands and fuzzy capacities. IEEE Trans Syst Man Cybern Part A Syst Hum 33(3):302–313

    Article  Google Scholar 

  • Hausman W, Mcclain J (1971) A note on the Bergstrom-Smith multi-item production planning model. Manag Sci 17(11):783–785

    Article  Google Scholar 

  • Holt C, Modigliani F, Simon H (1955) A linear decision rule for production and employment scheduling. Manag Sci 2(1):1–30

    Article  Google Scholar 

  • Kwakernaak H (1978) Fuzzy random variables-I: definition and theorems. Inf Sci 15(1):1–29

    Article  MathSciNet  MATH  Google Scholar 

  • Kwakernaak H (1979) Fuzzy random variables-II: algorithms and examples for the discrete case. Inf Sci 17(3):253–278

    Article  MathSciNet  MATH  Google Scholar 

  • Li X, Chien C, Li L, Gao ZY, Yang L (2012a) Energy-constraint operation strategy for high-speed railway. Int J Innov Comput Inf Control 8(10):6569–6583

    Google Scholar 

  • Li X, Wang D, Li K, Gao Z (2012b) A green train scheduling model and fuzzy multi-objective optimization algorithm. Appl Math Model. doi:10.1016/j.apm.2012.04.046

  • Liu B (2001a) Fuzzy random chance-constrained programming. IEEE Trans Fuzzy Syst 9(5):713–720

    Article  Google Scholar 

  • Liu B (2001b) Fuzzy random dependent-chance programming. IEEE Trans Fuzzy Syst 9(5):721–726

    Article  Google Scholar 

  • Liu B (2007) Uncertainty theory, 2nd edn. Springer, Berlin

  • Liu B (2009a) Some research problems in uncertainty theory. J Uncertain Syst 3(1):3–10

    Google Scholar 

  • Liu B (2009b) Theory and practice of uncertain programming, 2nd edn. Springer, Berlin

  • Liu B (2010a) Uncertainty theory: a branch of mathematics for modeling human uncertainty. Springer, Berlin

    Google Scholar 

  • Liu B (2010b) Uncertain risk analysis and uncertain reliability analysis. J Uncertain Syst 4(3):163–170

    Google Scholar 

  • Liu B (2012) Why is there a need for uncertainty theory? J Uncertain Syst 6(1):3–10

    Google Scholar 

  • Liu J (2011) Uncertain comprehensive evaluation method. J Inf Comput Sci 8(2):336–344

    Google Scholar 

  • Liu Y, Chen XW (2012) Uncertain currency model and currency option pricing. http://orsc.edu.cn/online/091010.pdf

  • Liu Y, and Ha MH (2010) Expected value of function of uncertain variables. J Uncertain Syst 4(3):181–186

    Google Scholar 

  • Ning Y, Tang W, and Zhao R (2006) Multiproduct aggregate production planning in fuzzy random environments. World J Model Simul 2(5):312–321

    Google Scholar 

  • Ramezanian R, Rahmani D, and Barzinpour F (2012) An aggregate production planning model for two phase production systems: Solving with genetic algorithm and tabu search. Expert Syst Appl 39(1):1256–1263

    Article  Google Scholar 

  • Rong LX (2011) Two new uncertainty programming models of inventory with uncertain costs. J Inf Comput Sci 8(2):280–288

    Google Scholar 

  • Wang R, and Fang H (2001) Aggregate production planning with multiple objectives in a fuzzy environment. Eur J Oper Res 133(3):521–536

    Article  MATH  Google Scholar 

  • Wang R, and Liang T (2005) Applying possibilistic linear programming to aggregate production planning. Int J Prod Econ 98(3):328–341

    Article  Google Scholar 

  • Yan LM (2009) Optimal portfolio selection models with uncertain returns. Modern Appl Sci 3(8):76–81

    MATH  Google Scholar 

  • Yang L, Li K, Gao Z (2009) Train timetable problem on a single-line railway with fuzzy passenger demand. IEEE Trans Fuzzy Syst 17(3):617–629

    Article  Google Scholar 

  • Yang L, Gao Z, Li K, Li X (2012) Optimizing trains movement on a railway network. Omega Int J Manag Sci 40:619–633

    Article  Google Scholar 

  • Zhang R, Zhang L, Xiao Y, Kaku I (2012) The activity-based aggregate production planning with capacity expansion in manufacturing systems. Comput Ind Eng 62(2):491–503

    Article  Google Scholar 

Download references

Acknowledgments

This paper is supported by Shandong Provincial Scientific and Technological Research Plan Project (No. 2009GG20001029).

Author information

Authors and Affiliations

  1. Department of Computer Science, Dezhou University, Dezhou, 253023, China

    Yufu Ning & Jianjun Liu

  2. Department of Mathematics, Dezhou University, Dezhou, 253023, China

    Limei Yan

Authors
  1. Yufu Ning
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jianjun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Limei Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yufu Ning.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ning, Y., Liu, J. & Yan, L. Uncertain aggregate production planning. Soft Comput 17, 617–624 (2013). https://doi.org/10.1007/s00500-012-0931-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-012-0931-4

Keywords

Search

Navigation