Skip to main content
Log in

Flow shop scheduling with peak power consumption constraints

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

Abstract

We study scheduling as a means to address the increasing energy concerns in manufacturing enterprises. In particular, we consider a flow shop scheduling problem with a restriction on peak power consumption, in addition to the traditional time-based objectives. We investigate both mathematical programming and combinatorial approaches to this scheduling problem, and test our approaches with instances arising from the manufacturing of cast iron plates.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Algorithm 3.1
Algorithm 3.2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Albers, S. (2010). Energy-efficient algorithms. Communications of the ACM, 53(5), 86–96.

    Article  Google Scholar 

  • Babu, C. A., & Ashok, S. (2008). Peak load management in electrolytic process industries. IEEE Transactions on Power Systems, 23(2), 399–405.

    Article  Google Scholar 

  • Bansal, N., Kimbrel, T., & Pruhs, K. (2007). Speed scaling to manage energy and temperature. Journal of the ACM, 54(1), 1–39.

    Article  Google Scholar 

  • Bansal, N., Chan, H. L., & Pruhs, K. (2009). Speed scaling with an arbitrary power function. In Proceedings of the 20th annual ACM-SIAM symposium on discrete algorithms (pp. 693–701).

    Google Scholar 

  • Bouzid, W. (2005). Cutting parameter optimization to minimize production time in high speed turning. Journal of Materials Processing Technology, 161(3), 388–395.

    Article  Google Scholar 

  • Cochran, R., Hankendi, C., Coskun, A., & Reda, S. (2011). Pack & cap: adaptive DVFS and thread packing under power caps. In Proceedings of the 44th annual IEEE/ACM international symposium on microarchitecture.

    Google Scholar 

  • Dahmus, J. B., & Gutowski, T. G. (2004). An environmental analysis of machining. In ASME 2004 international mechanical engineering congress and exposition (pp. 643–652).

    Google Scholar 

  • Demidenko, V. M. (1979). The traveling salesman problem with asymmetric matrices. Izvestiâ Akademii Nauk BSSR. Seriâ Fiziko-Matematičeskih Nauk, 1, 29–35 (in Russian).

    Google Scholar 

  • Drake, R., Yildirim, M. B., Twomey, J., Whitman, L., Ahmad, J., & Lodhia, P. (2006). Data collection framework on energy consumption in manufacturing. In IIE annual conference and expo 2006.

    Google Scholar 

  • Fang, K., Uhan, N. A., Zhao, F., & Sutherland, J. W. (2011). A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction. Journal of Manufacturing Systems, 30(4), 234–240.

    Article  Google Scholar 

  • Felter, W., Rajamani, K., Keller, T., & Rusu, C. (2005). A performance-conserving approach for reducing peak power consumption in server systems. In Proceedings of the 19th annual international conference on supercomputing (pp. 293–302).

    Chapter  Google Scholar 

  • Garey, M. R., Johnson, D. S., & Sethi, R. (1976). The complexity of flowshop and jobshop scheduling. Mathematics of Operations Research, 1(2), 117–129.

    Article  Google Scholar 

  • Gutowski, T., Murphy, C., Allen, D., Bauer, D., Bras, B., Piwonka, T., Sheng, P., Sutherland, J., Thurston, D., & Wolff, E. (2005). Environmentally benign manufacturing: observations from Japan, Europe and the United States. Journal of Cleaner Production, 13, 1–17.

    Article  Google Scholar 

  • Irani, S., & Pruhs, K. R. (2005). Algorithmic problems in power management. SIGACT News, 36(2), 63–76.

    Article  Google Scholar 

  • Keha, A. B., Khowala, K., & Fowler, J. W. (2009). Mixed integer programming formulations for single machine scheduling problems. Computers & Industrial Engineering, 56(1), 357–367.

    Article  Google Scholar 

  • Kontorinis, V., Shayan, A., Tullsen, D. M., & Kumar, R. (2009). Reducing peak power with a table-driven adaptive processor core. In Proceedings of the 42nd annual IEEE/ACM international symposium on microarchitecture (pp. 189–200).

    Chapter  Google Scholar 

  • Kwon, W. C., & Kim, T. (2005). Optimal voltage allocation techniques for dynamically variable voltage processors. ACM Transactions on Embedded Computing Systems, 4(1), 211–230.

    Article  Google Scholar 

  • Lasserre, J. B., & Queyranne, M. (1992). Generic scheduling polyhedra and a new mixed-integer formulation for single-machine scheduling. In Proceedings of the 2nd integer programming and combinatorial optimization conference (pp. 136–149).

    Google Scholar 

  • Manne, A. S. (1960). On the job-shop scheduling problem. Operations Research, 8(2), 219–223.

    Article  Google Scholar 

  • Mouzon, G., & Yildirim, M. B. (2008). A framework to minimise total energy consumption and total tardiness on a single machine. International Journal of Sustainable Engineering, 1(2), 105–116.

    Article  Google Scholar 

  • Mouzon, G., Yildirim, M. B., & Twomey, J. (2007). Operational methods for minimization of energy consumption of manufacturing equipment. International Journal of Production Research, 45(18–19), 4247–4271.

    Article  Google Scholar 

  • Mudge, T. (2001). Power: a first-class architectural design constraint. Computer, 34(4), 52–58.

    Article  Google Scholar 

  • Oberg, E., Jones, F. D., Horton, H. L., & Ryffel, H. H. (2008). Machinery’s handbook (28th ed.). New York: Industrial Press.

    Google Scholar 

  • Reddi, S. S., & Ramamoorthy, C. V. (1972). On the flow-shop sequencing problem with no wait in process. Operational Research Quarterly, 23(3), 323–331.

    Article  Google Scholar 

  • Stafford, E. F. Jr., Tseng, F. T., & Gupta, J. N. D. (2005). Comparative evaluation of MILP flowshop models. Journal of the Operational Research Society, 56, 88–101.

    Article  Google Scholar 

  • Thörnblad, K., Strömberg, A. B., & Patriksson, M. (2010). Optimization of schedules for a multitask production cell. In The 22nd annual NOFOMA conference proceedings.

    Google Scholar 

  • Unlu, Y., & Mason, S. J. (2010). Evaluation of mixed integer programming formulations for non-preemptive parallel machine scheduling problems. Computers & Industrial Engineering, 58(4), 785–800.

    Article  Google Scholar 

  • Wagner, H. M. (1959). An integer linear-programming model for machine scheduling. Naval Research Logistics Quarterly, 6(2), 134–140.

    Article  Google Scholar 

  • Yao, F., Demers, A., & Shenker, S. (1995). A scheduling model for reduced CPU energy. In Proceedings of the 36th annual symposium on foundations of computer science (pp. 374–382).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nelson A. Uhan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fang, K., Uhan, N.A., Zhao, F. et al. Flow shop scheduling with peak power consumption constraints. Ann Oper Res 206, 115–145 (2013). https://doi.org/10.1007/s10479-012-1294-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-012-1294-z

Keywords

Navigation