Skip to main content
Log in

An agent-based algorithm for personnel shift-scheduling and rescheduling in flexible assembly lines

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

This article is about a multi-agent based algorithm for personnel scheduling and rescheduling in a dynamic environment of a paced multi-product assembly center. The purpose is first to elaborate daily employees’ assignment to workstations so as to minimize the operational costs as well as personnel dissatisfactions; the second is to generate an alternative planning when the first solution has to be rescheduled due to disturbances related to absenteeism. The proposed approach takes into account individual competencies, mobility and preferences of each employee, along with the competency requirements associated with each assembly activity, with respect to both the current master assembly schedule and the line balancing for each product. We use solutions obtained through a simulated annealing algorithm in order to benchmark the performance of the multi-agent approach. Experimental results show that our multi-agent approach can produce high-quality and efficient solutions in a short computational time.

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

  • Aickelin U., Dowsland K. (2000) Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem. Journal of Scheduling 3: 139–153

    Article  Google Scholar 

  • Atlason J., Epelman M. A. (2004) Call center staffing with simulation and cutting plan. Annals of Operations Research 127: 333–358

    Article  Google Scholar 

  • Bailey J., Field J. (1985) Personnel scheduling with flexshift models. Journal of Operations Management 5: 327–338

    Article  Google Scholar 

  • Baker K. (1976) Workforce allocation in cyclical scheduling problems, A survey. Operational Research Quarterly 27: 155–167

    Article  Google Scholar 

  • Bartholdi J. (1981) A guaranteed-accuracy round-off algorithm for cyclic scheduling and set covering. Operations Research 29: 501–510

    Article  Google Scholar 

  • Berman O., Larson R.C., Pinker E. (1997) Scheduling workforce and workflow in a high volume factory. Management Science 43: 158–172

    Article  Google Scholar 

  • Brusco M. J., Jacobs L. W., Bongiorno R. J., Lyons D., Tang B. (1995) Improving personnel scheduling at airline stations. Operations Research 43: 741–751

    Article  Google Scholar 

  • Brusco M. J., Jacobs L. W. (1998) Personnel tour scheduling when starting-time restrictions are present. Management Science 44: 534–547

    Article  Google Scholar 

  • Davis M., Maschler M. (1965) The kernel of a cooperative game. Naval research Logistics Quarterly 12: 223–259

    Article  Google Scholar 

  • DeGans O. B. (1981) A computer timetabling system for secondary schools in the Netherlands. European Journal of Operational Research 7: 175–182

    Article  Google Scholar 

  • Duffie N. A., Piper R. S. (1986) Non-hierarchical control of manufacturing systems. Journal of Manufacturing Systems 5: 39–137

    Article  Google Scholar 

  • Easton F. F., Mansour N. (1999) A distributed genetic algorithm for deterministic and stochastic labor scheduling problems. European Journal Of Operational Research 118: 505–523

    Article  Google Scholar 

  • Easton F. F., Rossin D. F. (1996) A stochastic goal program for employee scheduling. Decision Sciences 27: 541–568

    Article  Google Scholar 

  • Ernst A. T., Jiang H., Krishnamoorthy M., Sier D. (2004) Staff scheduling and rostering: A review of applications, methods and models. European Journal of Operational Research 153: 3–27

    Article  Google Scholar 

  • Frayret J.-M., D’Amours S., Rousseau A., Harvey S., Gaudreault J. (2007) Agent-based supply chain planning in the forest products industry. International Journal of Flexible Manufacturing Systems 19(4): 358–391

    Article  Google Scholar 

  • Garey M.R., Johnson D.S. (1979) Computers and intractability, a guide to the theory of NP-completeness. WH Freeman & Co, New York

    Google Scholar 

  • Gokturk, E., & Polat, F. (2003). Implementing agent communication for a multiagent simulation infrastructure. In On HLA. Proceedings of the international symposium on computer and information science, LNCS, Springer, New York.

  • Hao G., Lai K. K., Tan M. (2004) A neural network application in personnel scheduling. Annals of Operations Research 128: 65–90

    Article  Google Scholar 

  • Kouiss K., Pierreval H., Mebarki N. (1997) Using multi-agent architecture in FMS for dynamic scheduling. Journal of Intelligent Manufacturing 8(1): 41–47

    Article  Google Scholar 

  • Lee C., Vairaktarakis G. (1997) Workforce planning in mixed model assembly systems. Operations Research 45(4): 553–567

    Article  Google Scholar 

  • Lesser V. R. (1999) Cooperative multiagent systems: A personal view of the state of the art. IEEE Transactions on Knowledge and Data Engineering 11(1): 133–142

    Article  Google Scholar 

  • Maturana F., Norrie D. (1996) Multi-agent mediator architecture for distributed manufacturing. Journal of Intelligent Manufacturing 7: 257–270

    Article  Google Scholar 

  • Miyashita K. (1998) CAMPS: A constraint-based architecture for multi-agent planning and scheduling. Journal of Intelligent Manufacturing 9(2): 147–154

    Article  Google Scholar 

  • Montreuil B., Poulin M. (2005) Demand and supply network design scope for personalised manufacturing. Production Planning & Control 15: 454–469

    Article  Google Scholar 

  • Monostori L., Vancza J., Kumara S. R. T. (2006) Agent-based systems for manufacturing. CIRP Annals-Manufacturing Technology 55: 697–720

    Article  Google Scholar 

  • Oliveira E., Fischer K., Stepankova O. (1999) Multi-agent systems: Which research for which applications. Robotics and Autonomous Systems 27: 91–106

    Article  Google Scholar 

  • Parunak H. V. D., Baker A. D., Clark S. J. (2001) The AARIA agent architecture: From manufacturing requirements to agent-based system design. Integrated Computer-Aided Engineering 8: 45–58

    Google Scholar 

  • Rapoport A. (1970) N-person game theory: Concepts and applications. University of Michigan Press, Michigan

    Google Scholar 

  • Russell, S. J., & Zilberstein, S. (1991). Composing real-time systems. In Proceedings of the twelfth international conference on artificial intelligence, pp. 212–217.

  • Russel S., Norvig P. (1995) Artificial intelligence: A modern approach. Prentice Hall, New Jersey

    Google Scholar 

  • Sabar M., Montreuil B., Frayret J. -M. (2008) Competency and preference based personnel scheduling in large assembly lines. International Journal of Computer Integrated Manufacturing 21: 468–479

    Article  Google Scholar 

  • Sabar, M. (2008). A multi-agent based approach for personnel scheduling in assembly centers. Doctoral Thesis, Université Laval, Canada

  • Sabar M., Montreuil B., Frayret J. -M. (2009) A multi-agent-based approach for personnel scheduling in assembly centers. Engineering Applications of Artificial Intelligence 22(7): 1080–1088

    Article  Google Scholar 

  • Shen W., Hao Q., Yoon H. J., Norrie D. H. (2006) Applications of agent-based systems in intelligent manufacturing: An updated review. Advanced Engineering Informatics 20: 415–431

    Article  Google Scholar 

  • Shen W., Norrie D.H. (1998) An agent-based approach for distributed manufacturing and supply chain management. In: Jacucci G (eds) Globalization of manufacturing in the digital communications era of the 21st century: Innovation, agility, and the virtual enterprise. Kluwer Academic Publishers, Boston

    Google Scholar 

  • Stearns R. E. (1968) Convergent transfer schemes for N-person games. Transactions of the American Mathematical Society 134: 449–459

    Google Scholar 

  • Thompson G. M. (1995) Improved implicit optimal modeling of the labor shift scheduling problem. Management Science 41: 595–607

    Article  Google Scholar 

  • Topaloglu S., Ozkarahan I. (2004) An implicit goal programming model for the tour-scheduling problem considering the employee work preferences. The Annals of OR Special Issue on Staff Scheduling and Rostering 128: 135–150

    Google Scholar 

  • Vairaktarakis G., Kim Winch J. (1999) Worker cross-training in paced assembly lines. Manufacturing & Service Operations Management 1(2): 112–131

    Article  Google Scholar 

  • Volgenant A. (2004) A note on the assignment problem with seniority and job priority constraints. European Journal of Operational Research 154: 330–335

    Article  Google Scholar 

  • Wooldridge M. (2002) An introduction to multi-agent systems. Wiley, Chichester

    Google Scholar 

  • Wooldridge M., Jennings N. (1995) Intelligent agents: Theory and practice. Knowledge Engineering Review 10(2): 115–152

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Sabar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sabar, M., Montreuil, B. & Frayret, JM. An agent-based algorithm for personnel shift-scheduling and rescheduling in flexible assembly lines. J Intell Manuf 23, 2623–2634 (2012). https://doi.org/10.1007/s10845-011-0582-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-011-0582-9

Keywords

Navigation