A Mockup Stochastic Program to Study the Impact of Design Uncertainty on ETO Shipbuilding Planning

  • Hajnalka Vaagen
  • Michal Kaut
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 460)


A major driver of planning complexity in dynamically changing ETO shipbuilding is design uncertainty far into the design planning and production processes. This leads to uncertainty in task and project completion time, and complex dependencies and correlations driven by the uncertainty in multiple task parameters. The problem is difficult to be solved exactly, and decision-making is largely based on experience and gut feeling, with subsequent behavioral challenges. We build a mockup stochastic program to draw attention to- and analyze the complexity of formulating and solving the engineering design planning problem. We demonstrate how design uncertainty is affecting the planning complexity and solutions.


ETO Project planning Stochastic programming 



This paper is part of the competence building research project NextShip, under Norwegian Research Council grant agreement 216418/O70.


  1. 1.
    Emblemsvag, J.: Lean project planning in shipbuilding. J. Ship Prod. Des. 30(2), 79–88 (2014)CrossRefGoogle Scholar
  2. 2.
    Jørgensen, T., Wallace, S.W.: Improving project cost estimation by taking into account managerial flexibility. Eur. J. Oper. Res. 127, 239–251 (2000)CrossRefGoogle Scholar
  3. 3.
    King, A.J., Wallace, S.W.: Modeling with Stochastic Programming. Springer Series in Operations Research and Financial Engineering. Springer, New York (2012)zbMATHCrossRefGoogle Scholar
  4. 4.
    Lium, A.G., Crainic, T.G., Wallace, S.W.: A study of demand stochasticity in stochastic network design. Transp. Sci. 43(2), 144–157 (2009)CrossRefGoogle Scholar
  5. 5.
    Morris, P.W.G.: The Management of Projects. Thomas Telford, London (1994)CrossRefGoogle Scholar
  6. 6.
    Rolstadas, A., Pinto, J.K., Falster, P., Venkataraman, R.: Decision Making in Project management. NTNU Engineering Series. Fagbokforlaget, Bergen (2014)Google Scholar
  7. 7.
    Schuyler, J.R.: Risk and Decision Analysis in Projects. Project Management Institute, Newton Square (2001)Google Scholar
  8. 8.
    Vaagen, H., Aas, B.: A multidisciplinary framework for robust planning and decision-making in dynamically changing engineering construction projects. In: Grabot, B., Vallespir, B., Gomes, S., Bouras, A., Kiritsis, D. (eds.) Advances in Production Management Systems. IFIP AICT, vol. 438, pp. 515–522. Springer, Heidelberg (2014)Google Scholar
  9. 9.
    Vaagen, H., Wallace, S.W., Kaut, M.: Modelling consumer-directed substitution. Int. J. Prod. Econ. 134(2), 388–397 (2011)CrossRefGoogle Scholar
  10. 10.
    Vaagen, H., Wallace, S.W.: Product variety arising from hedging in the fashion supply chains. Int. J. Prod. Econ. 114(2), 431–455 (2008)CrossRefGoogle Scholar
  11. 11.
    Wall, D.M.: Distributions and correlations in Monte Carlo simulation. Constr. Manage. Econ. 15(3), 241–258 (1997)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2015

Authors and Affiliations

  1. 1.Department of Applied EconomicsSINTEF Technology and SocietyTrondheimNorway

Personalised recommendations