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Solving multistage asset investment problems by the sample average approximation method

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Abstract

The vast size of real world stochastic programming instances requires sampling to make them practically solvable. In this paper we extend the understanding of how sampling affects the solution quality of multistage stochastic programming problems. We present a new heuristic for determining good feasible solutions for a multistage decision problem. For power and log-utility functions we address the question of how tree structures, number of stages, number of outcomes and number of assets affect the solution quality. We also present a new method for evaluating the quality of first stage decisions.

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Authors and Affiliations

  1. Department of Mathematics, Linköpings universitet, Linköping, 58183, Sweden

    Jörgen Blomvall

  2. School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, 30332-0205, USA

    Alexander Shapiro

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  1. Jörgen Blomvall
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  2. Alexander Shapiro
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Correspondence to Jörgen Blomvall.

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Blomvall, J., Shapiro, A. Solving multistage asset investment problems by the sample average approximation method. Math. Program. 108, 571–595 (2006). https://doi.org/10.1007/s10107-006-0723-7

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  • DOI: https://doi.org/10.1007/s10107-006-0723-7

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