A Reformulation-Linearization Technique for Solving Discrete and Continuous Nonconvex Problems - Tapa blanda

Sinopsis

Preface. 1. Introduction. Part I: Discrete Nonconvex Programs. 2. RLT Hierarchy for Mixed-Integer Zero-One Problems. 3. Generalized Hierarchy for Exploiting Special Structures in Mixed-Integer Zero-One Problems. 4. RLT Hierarchy for General Discrete Mixed-Integer Problems. 5. Generating Valid Inequalities and Facets Using RLT. 6. Persistency in Discrete Optimization. Part II: Continuous Nonconvex Programs. 7. RLT-Based Global Optimization Algorithms for Nonconvex Polynomial Programming Problems. 8. Reformulation-Convexification Technique for Quadratic Programs and Some Convex Envelope Characterizations. 9. Reformulation-Convexification Technique for Polynomial Programs: Design and Implementation. Part III: Special Applications to Discrete and Continuous Nonconvex Programs. 10. Applications to Discrete Problems. 11. Applications to Continuous Problems. References.

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