Certifiable Global Optimality for Large-Scale Nonconvex Mixed-Integer Programs
Mixed-Integer Nonlinear Programming (MINLP) problems are ubiquitous in science and engineering, modeling complex systems where decisions are both continuous and discrete, and relationships are nonlinear. However, the presence of nonconvexity and large-scale structures presents significant challenges to obtaining and, crucially, certifying global ...
Revista, Zen, MATH, 10
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Based on theoretical and algorithmic tools of DC programming and DCA, the research in this thesis focus on the local and global approaches for non convex optimization and global mixed integer optimization. The thesis consists of 5 chapters. The first chapter presents fundamentals of DC programming and DCA, and techniques of Branch and Bound method (B&B)
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