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Titlebook: Disjunctive Programming; Egon Balas Book 2018 Springer Nature Switzerland AG 2018 optimization.integer programming.nonconvex programming.l

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楼主: Conjecture
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Saroja Ramanujan,Kapil Gadkar,Ananth KadambiThe major practical consequence of the correspondence established in Theorems 8.4A/8.4B is that the cut generating linear program (CGLP). need not be formulated and solved explicitly; instead, the procedure for solving it can be mimicked on the linear programming relaxation (LP) of the original mixed 0-1 problem.
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https://doi.org/10.1007/978-3-319-44534-2The discovery of the possibility of generating L&P cuts through pivoting in the LP tableau, without recourse to the higher-dimensional (CGLP), has opened the door to the introduction of this class of cuts into commercial optimizers
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https://doi.org/10.1007/978-1-4471-7351-9Given a disjunctive set in disjunctive normal form, i.e. as a union of polyhedra.
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Disjunctive Programming and Extended Formulations,The fact that the convex hull of a disjunctive set has a compact representation in a higher dimensional space has spurred interest in finding convenient higher dimensional representations of various combinatorial objects.
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Lift-and-Project Cuts for Mixed 0-1 Programs,Consider now the mixed 0-1 programming problem
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