An enhanced decomposition algorithm for multistage stochastic hydroelectric scheduling

David P. Morton*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


Handling uncertainty in natural inflow is an important part of a hydroelectric scheduling model. In a stochastic programming formulation, natural inflow may be modeled as a random vector with known distribution, but the size of the resulting mathematical program can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such problems. We develop an enhanced Benders decomposition algorithm for solving multistage stochastic linear programs. The enhancements include warm start basis selection, preliminary cut generation, the multicut procedure, and decision tree traversing strategies. Computational results are presented for a collection of stochastic hydroelectric scheduling problems.

Original languageEnglish (US)
Pages (from-to)211-235
Number of pages25
JournalAnnals of Operations Research
StatePublished - Jan 1 1996


  • Hydroelectric scheduling
  • Large-scale systems
  • Stochastic programming

ASJC Scopus subject areas

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

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