Skip to main content
Log in

A Lagrangian approach to single-machine scheduling problems with two competing agents

  • Published:
Journal of Scheduling Aims and scope Submit manuscript

Abstract

In this paper, we develop branch-and-bound algorithms for several hard, two-agent scheduling problems, i.e., problems in which each agent has an objective function which depends on the completion times of its jobs only. Our bounding approach is based on the fact that, for all problems considered, the Lagrangian dual gives a good bound and can be solved exactly in strongly polynomial time. The problems addressed here consist in minimizing the total weighted completion time of the jobs of agent A, subject to a bound on the cost function of agent B, which may be: (i) total weighted completion time, (ii) maximum lateness, (iii) maximum completion time. An extensive computational experience shows the effectiveness of the approach.

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

  • Albino, V., Carbonara, N., & Giannoccaro, I. (2006). Innovation in industrial districts: an agent-based simulation model. International Journal of Production Economics, 104, 30–45.

    Article  Google Scholar 

  • Arbib, C., Servilio, M., & Smriglio, S. (2004). A competitive scheduling problem and its relevance to UMTS channel assignment. Networks, 44(2), 132–141.

    Article  Google Scholar 

  • Agnetis, A., Mirchandani, P. B., Pacciarelli, D., & Pacifici, A. (2000). Nondominated schedules for a job-shop with two competing agents. Computational and Mathematical Organization Theory, 6(2), 191–217.

    Article  Google Scholar 

  • Agnetis, A., Mirchandani, P. B., Pacciarelli, D., & Pacifici, A. (2004). Scheduling problems with two competing agents. Operations Research, 52(2), 229–242.

    Article  Google Scholar 

  • Baker, K. R., & Cole Smith, J. (2003). A multiple-criterion model for machine scheduling. Journal of Scheduling, 6(1), 7–16.

    Article  Google Scholar 

  • Cheng, T. C. E., Ng, C. T., & Yuan, J. J. (2006). Multi-agent scheduling on a single machine to minimize total weighted number of tardy jobs. Theoretical Computer Science, 362, 273–281.

    Article  Google Scholar 

  • Cheng, T. C. E., Ng, C. T., & Yuan, J. J. (2008). Multi-agent scheduling on a single machine with max-form criteria. European Journal of Operational Research, 188, 603–609.

    Article  Google Scholar 

  • Ng, C. T., Cheng, T. C. E., & Yuan, J. J. (2006). A note on the complexity of the problem of two-agent scheduling on a single machine. Journal of Combinatorial Optimization, 12(4), 387–394.

    Article  Google Scholar 

  • Pan, Y. (2003). An improved branch and bound algorithm for single machine scheduling with deadlines to minimize total weighted completion time. Operations Research Letters, 31, 492–496.

    Article  Google Scholar 

  • Peha, J. M. (1995). Heterogeneous-criteria scheduling: minimizing weighted number of tardy jobs and weighted completion time. Journal of Computers and Operations Research, 22(10), 1089–1100.

    Article  Google Scholar 

  • Posner, M. E. (1985). Minimizing weighted completion times with deadlines. Operations Research, 33(3), 562–574.

    Article  Google Scholar 

  • Smith, W. E. (1956). Various optimizers for single-stage production. Naval Research Logistics Quarterly, 3(1), 59–66.

    Article  Google Scholar 

  • Sourd, F. (2008). Private communication.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alessandro Agnetis.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Agnetis, A., de Pascale, G. & Pacciarelli, D. A Lagrangian approach to single-machine scheduling problems with two competing agents. J Sched 12, 401–415 (2009). https://doi.org/10.1007/s10951-008-0098-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10951-008-0098-0

Keywords

Navigation