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fengqiao luo(fengqiaoluo2014u.northwestern.edu) Abstract: We consider a general mixedinteger convex program. We first develop an algorithm for solving this problem, and show its nite convergence. We then develop a finitely convergent decomposition algorithm that separates binary variables from integer and continuous variables. The integer and continuous variables are treated as second stage variables. An oracle for generating a parametric cut under a subgradient decomposition assumption is developed. The decomposition algorithm is applied to show that twostage (distributionally robust) convex programs with binary variables in the first stage can be solved to optimality within a cutting plane framework. For simplicity, the paper assumes that certain convex programs generated in the course of the algorithm are solved to optimality. Keywords: cutting planes, finite convergence, twostage mixedinteger convex programming, Bender's decomposition method Category 1: Integer Programming ((Mixed) Integer Nonlinear Programming ) Category 2: Integer Programming (Cutting Plane Approaches ) Category 3: Stochastic Programming Citation: Download: [PDF] Entry Submitted: 12/08/2021 Modify/Update this entry  
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