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Decomposition Methods

Decomposition Methods. Lecture 6. Leonidas Sakalauskas Institute of Mathematics and Informatics Vilnius, Lithuania EURO Working Group on Continuous Optimization. Content. Constraint matrix block systems Benders decomposition Master problem and cuts Dantzig-Wolfe decomposition

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Decomposition Methods

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  1. Decomposition Methods Lecture 6 Leonidas Sakalauskas Institute of Mathematics and Informatics Vilnius, Lithuania EURO Working Group on Continuous Optimization

  2. Content • Constraint matrix block systems • Benders decomposition • Master problem and cuts • Dantzig-Wolfe decomposition • Comparison of Benders and Dantzig-Wolfe decompositions

  3. Two-stage SLP The two-stage stochastic linear programming problem can be stated as

  4. Two-Stage SLP Assume the set of scenarios K be finite and defibed by probabilities In continuous stochastic programming by the Monte-Carlo Method this is equivalent to

  5. Two-Stage SLP Using the definition of discrete random variable the SLP considered is equivalent to large linear problem with block constraint matrix:

  6. Block Diagonal

  7. Staircase Systems

  8. Block Angular

  9. Benders Decomposition

  10. Feasibility

  11. Dantzif-Wolfe Decomposition Primal Block Angular Structure

  12. The Problem

  13. Wrap-Up and conclusions • The discrete SLP is reduced to equivalent linear program with block constraint matrix, that solved by Benders or Dantzig-Wolfe decomposition method • The continuous SLP is solved by decomposition method simulating the finite set of random scenarios

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