Annals of Operations Research

, Volume 20, Issue 1, pp 187–217 | Cite as

Stochastic network optimization models for investment planning

  • John M. Mulvey
  • Hercules Vladimirou


We describe and compare stochastic network optimization models for investment planning under uncertainty. Emphasis is placed on multiperiod a sset allocation and active portfolio management problems. Myopic as well as multiple period models are considered. In the case of multiperiod models, the uncertainty in asset returns filters into the constraint coefficient matrix, yielding a multi-scenario program formulation. Different scenario generation procedures are examined. The use of utility functions to reflect risk bearing attitudes results in nonlinear stochastic network models. We adopt a newly proposed decomposition procedure for solving these multiperiod stochastic programs. The performance of the models in simulations based on historical data is discussed.


Utility Function Stochastic Program Program Formulation Asset Return Portfolio Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© J.C. Baltzer AG, Scientific Publishing Company 1989

Authors and Affiliations

  • John M. Mulvey
    • 1
  • Hercules Vladimirou
    • 1
  1. 1.School of Engineering and Applied SciencesPrinceton UniversityPrincetonUSA

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