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Assessing Solution Quality in Stochastic Programs via Sampling
[chapter]
2009
Decision Technologies and Applications
Determining if a solution is optimal or near optimal is fundamental in optimization theory, algorithms, and computation. For instance, Karush-Kuhn-Tucker conditions provide necessary and sufficient optimality conditions for certain classes of problems, and bounds on optimality gaps are frequently used as part of optimization algorithms. Such bounds are obtained through Lagrangian, integrality, or semidefinite programming relaxations. An alternative approach in stochastic programming is to use
doi:10.1287/educ.1090.0065
fatcat:6tofe76lpje4bol2n6lrkjfxnu