Skip to main content

Advertisement

SpringerLink
Log in

Optimal production scheduling for the dairy industry

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

The increasing variety of products offered by the food industry has helped the industry to respond to market trends, but at the same time has resulted in a more complex production process, which requires flexibility and an efficient coordination of existing resources. Especially in industrial yogurt production, there is a wide variety of products that differ in features like fat content, the whey used to produce the mixture, the flavor, the size of the container or the language on the label. The great diversification and the special features that characterize yogurt production lines (satisfaction of multiple due dates, variable processing times, sequence-dependent setup times and costs and monitoring of inventory levels), render generic scheduling methodologies impractical for real-world applications. In this work we present a customized Mixed Integer Linear Programming (MILP) model for optimizing yogurt packaging lines that consist of multiple parallel machines. The model is characterized by parsimony in the utilization of binary variables and necessitates the use of only a small pre-determined number of time periods. The efficiency of the proposed model is illustrated through its application to the yogurt production plant of a leading dairy product manufacturing company in Greece.

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

  • Allahverdi, A., Gupta, J. N. D., & Aldowaisan, T. (1999). A review of scheduling research involving setup considerations. Omega, 27(2), 219–239.

    Article  Google Scholar 

  • Bureau, G., & Multon, J.-L. (1996). Food packaging technology. New York: Wiley-VCH.

    Google Scholar 

  • Chen, C., Liu, C., Feng, X., & Shao, H. (2002). Optimal short-term scheduling of multiproduct single-stage batch plants with parallel lines. Industrial Engineering & Chemistry Research, 41, 1249–1260.

    Article  Google Scholar 

  • Giannelos, N. F., & Georgiadis, M. C. (2003). Efficient scheduling of consumer goods manufacturing processes in the continuous time domain. Computers & Operations Research, 30(9), 1367–1381.

    Article  Google Scholar 

  • Gupta, S., & Karimi, I. A. (2003). An improved MILP formulation for sheduling multiproduct, multistage batch plants. Industrial Engineering & Chemistry Research, 42, 2365–2380.

    Article  Google Scholar 

  • Janak, S. L., Lin, X., & Floudas, C. A. (2004). Enhanced continuous-time unit-specific event-based formulation for short-term scheduling of multipurpose batch processes: Resource constraints and mixed storage policies. Industrial Engineering & Chemistry Research, 43(10), 2516–2533.

    Article  Google Scholar 

  • Kang, S., Malik, K., & Thomas, L. J. (1999). Lotsizing and scheduling on parallel machines with sequence-dependent setup costs. Management Science, 45(2), 273–289.

    Article  Google Scholar 

  • Karimi, I. A., & McDonald, C. M. (1997). Planning and scheduling of parallel semicontinuous processes. 2. Short-term scheduling. Industrial Engineering & Chemistry Research, 36(7), 2701–2714.

    Article  Google Scholar 

  • Kessler, H. G. (1981). Food engineering and dairy technology. Munich: Kessler.

    Google Scholar 

  • Lamba, N., & Karimi, I. A. (2002). Scheduling parallel production lines with resource constraints. 1. Model formulation. Industrial Engineering & Chemistry Research, 41, 779–789.

    Article  Google Scholar 

  • Lim, M.-F., & Karimi, I. A. (2003). Resource-constrained scheduling of parallel production lines using asynchronous slots. Industrial Engineering & Chemistry Research, 42(26), 6832–6842.

    Article  Google Scholar 

  • McKay, K., Pinedo, M., & Webster, S. (2002). Practice-focused research issues for scheduling systems. Production and Operations Management, 11(2), 249–258.

    Article  Google Scholar 

  • Pinto, J. M., & Grossmann, I. E. (1998). Assignment and sequencing models for the scheduling of process systems. Annals of Operations Research, 81, 433–466.

    Article  Google Scholar 

  • Tahmassebi, T. (1996). Industrial experience with a mathematical-programming based system for factory systems planning/ scheduling. Computers & Chemical Engineering, 20(2), 1565–1570.

    Article  Google Scholar 

  • Varnam, A. H., & Sutherland, J. P. (1994). Milk and milk products: Technology, chemistry and microbiology. London: Chapman & Hall.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Chemical Engineering, National Technical University of Athens, 9 Heroon Polytechniou Street, Zografou Campus, Athens, 15780, Greece

    Philip Doganis & Haralambos Sarimveis

Authors
  1. Philip Doganis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haralambos Sarimveis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Haralambos Sarimveis.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Doganis, P., Sarimveis, H. Optimal production scheduling for the dairy industry. Ann Oper Res 159, 315–331 (2008). https://doi.org/10.1007/s10479-007-0285-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-007-0285-y

Keywords

Search

Navigation