Convergence of duality bound method in partly convex programming
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We discuss the convergence of a decomposition branch-and-bound algorithm using Lagrangian duality for partly convex programs in the general form. It is shown that this decomposition algorithm has all convergence properties as any known branch-and-bound algorithm in global optimization under usual assumptions. Thus, some strict assumptions discussed in the literature are avoidable.
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