An integrated scheduling and control model for multi-mode projects

Article

Abstract

In today’s highly competitive uncertain project environments, it is of crucial importance to develop analytical models and algorithms to schedule and control project activities so that the deviations from the project objectives are minimized. This paper addresses the integrated scheduling and control in multi-mode project environments. We propose an optimization model that models the dynamic behavior of projects and integrates optimal control into a practically relevant project scheduling problem. From the scheduling perspective, we address the discrete time/cost trade-off problem, whereas an optimal control formulation is used to capture the effect of project control. Moreover, we develop a solution algorithm for two particular instances of the optimal project control. This algorithm combines a tabu search strategy and nonlinear programming. It is applied to a large scale test bed and its efficiency is tested by means of computational experiments. To the best of our knowledge, this research is the first application of optimal control theory to multi-mode project networks. The models and algorithms developed in this research are targeted as a support tool for project managers in both scheduling and deciding on the timing and quantity of control activities.

Keywords

Project scheduling Project control Optimal control theory 

References

  1. Akkan C, Drexl A, Kimms A (2005) Network decomposition-based benchmark results for the discrete timecost tradeoff problem. Eur J Oper Res 165(2):339–358MATHCrossRefGoogle Scholar
  2. Bertsekas DP (2000) Dynamic programming and optimal control, 3rd edn. Athena ScientificGoogle Scholar
  3. Byrd RH, Nocedal J, Waltz RA (2006) Large-scale nonlinear optimization, chap KNITRO: an integrated package for nonlinear optimization. Springer, Berlin, pp 35–59Google Scholar
  4. De P, Dunne EJ, Ghosh JB, Wells CE (1995) The discrete time-cost tradeoff problem revisited. Eur J Oper Res 81(2):225–238MATHCrossRefGoogle Scholar
  5. De P, Dunne EJ, Ghosh JB, Wells CE (1997) Complexity of the discrete time/cost trade-off problem for project networks. Oper Res 45:302–306MathSciNetMATHCrossRefGoogle Scholar
  6. De Falco M, Macchiaroli R (1998) Timing of control activities in project planning. Int J Proj Manag 16(1):51–58CrossRefGoogle Scholar
  7. Gendreau M, Potvin JY (2005) Metaheuristics in combinatorial optimization. Ann Oper Res 140:189–213MathSciNetMATHCrossRefGoogle Scholar
  8. Glover F (1989) Tabu search part I. ORSA J Comput 1(3):190–206MATHCrossRefGoogle Scholar
  9. Hazır O, Erel E, Gunalay Y (2011) Robust optimization models for the discrete time/cost trade-off problem. Int J Prod Econ 130(1):87–95CrossRefGoogle Scholar
  10. Herroelen W, Leus R (2005) Project scheduling under uncertainty: survey and research potentials. Eur J Oper Res 165(2):289–306MathSciNetMATHCrossRefGoogle Scholar
  11. Kogan K, Raz T, Elitzur R (2002) Optimal control in homogeneous projects: analytically solvable deterministic cases. IIE Trans 34(1):63–75Google Scholar
  12. Kolisch R, Hartmann S (2006) Experimental investigation of heuristics for resource-constrained project scheduling: an update. Eur J Oper Res 174(1):23–37MATHCrossRefGoogle Scholar
  13. Kolisch R, Padman R (2001) An integrated survey of deterministic project scheduling. OMEGA Int J Manag Sci 29(3):249–272CrossRefGoogle Scholar
  14. Kulturel-Konak S, Norman BA, Coit DW, Smith AE (2004) Exploiting tabu search memory in constrained problems. Inf J Comput 16(3):241–254MathSciNetMATHCrossRefGoogle Scholar
  15. Nowicki E, Zdrzalka S (1984) Optimal control policies for resource allocation in an activity network. Eur J Oper Res 16(2):198–214MathSciNetMATHCrossRefGoogle Scholar
  16. Partovi F, Burton J (1993) Timing of monitoring and control of CPM projects. IEEE Trans Eng Manag 40(1):68–75CrossRefGoogle Scholar
  17. Raz T, Erel E (2000) Optimal timing of project control points. Eur J Oper Res 127(2):252–261MATHCrossRefGoogle Scholar
  18. Sethi S, Thompson G (2002) Optimal control theory: applications to management science and economics, 2 edn. Kluwer, BostonGoogle Scholar
  19. Taillard ED, Gambardella LM, Gendreau M, Potvin JY (2001) Adaptive memory programming: a unified view of metaheuristics. Eur J Oper Res 135(1):1–16MathSciNetMATHCrossRefGoogle Scholar
  20. Weglarz J (1981) Project scheduling with continuously-divisible, doubly constrained resources. Manag Sci 27(9):1040–1053MATHCrossRefGoogle Scholar
  21. Weglarz J, Jozefowska J, Mika M, Waligora G (2010) Project scheduling with finite or infinite number of activity processing modes a survey. Eur J Oper ResGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Industrial Engineering DepartmentÇankaya UniversityAnkaraTurkey
  2. 2.Department of Mechatronics EngineeringÇankaya UniversityAnkaraTurkey

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