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A Reformulation-Linearization Technique for Solving Discrete and Continuous Nonconvex Problems 124 [¿] Zieh mitThis book deals with the theory and applications of the Reformulation Linearization Convexification Technique (RL T) for solving nonconvex optimization problems. A unified treatment of discrete and continuous nonconvex programming problems is presented using this approach. In essence, the bridge between these two types of nonconvexities is made via a polynomial representation of discrete constraints. For example, the binariness on a 0 1 variable x .