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I am looking for papers or other resources that provide an accessible introduction to L-shaped methods/Benders decomposition for solving stochastic linear programming-ideally something focused more on the practical and implementation side. Birge and Louveaux's book on stochastic programming provides some good examples, but I find their explanations long-winded. What are some of the best resources for learning Benders decomposition?

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Given your emphasis on practical and implementation aspects, I think the following two lectures will interest you:

  1. Stochastic Programming Modeling by Jeff Linderoth (University of Wisconsin, Madison)

  2. Benders Decomposition for Solving Two-stage Stochastic Optimization Models by Jim Luedtke (University of Wisconsin, Madison)

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  • $\begingroup$ These two lectures look good, Thank you. I probably need more material, so will wait for others to add to the list $\endgroup$ – Moving in rhythm with OR Aug 5 at 13:01

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