Stochastic network optimization models for investment planning

John Michael Mulvey, Hercules Vladimirou

Research output: Contribution to journalArticle

61 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)187-217
Number of pages31
JournalAnnals of Operations Research
Volume20
Issue number1
DOIs
StatePublished - Dec 1 1989

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Management Science and Operations Research

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