Annals of Operations Research

, Volume 64, Issue 1, pp 211–235 | Cite as

An enhanced decomposition algorithm for multistage stochastic hydroelectric scheduling

  • David P. Morton


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.


Stochastic programming hydroelectric scheduling large-scale systems 


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Copyright information

© J.C. Baltzer AG, Science Publishers 1996

Authors and Affiliations

  • David P. Morton
    • 1
  1. 1.Graduate Program in Operations Research and Industrial Engineering, Department of Mechanical EngineeringThe University of Texas at AustinAustinUSA

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