Compact Extended Linear Programming Models

This book provides a handy, unified introduction to the theory of compact extended formulations of exponential-size integer linear programming (ILP) models. Compact extended formulations are equally powerful polynomial-sized models whose solutions do not require the implementation of separation and...

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Bibliographische Detailangaben
1. Verfasser: Lancia, Giuseppe (VerfasserIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Cham : Springer International Publishing, 2018.
Ausgabe:1st ed. 2018.
Schriftenreihe:EURO Advanced Tutorials on Operational Research,
Schlagworte:
ISBN:9783319639765
ISSN:2364-687X
Online-Zugang: Volltext
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245 1 0 |a Compact Extended Linear Programming Models  |h [electronic resource] /  |c by Giuseppe Lancia, Paolo Serafini. 
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500 |a Business and Management  
505 0 |a Introduction -- Polyhedra -- Linear Programming -- Integer Linear Programming -- Large-scale Linear Programming -- General Techniques for Compact Formulations -- The Permutahedron -- The Parity Polytope -- Trees -- Cuts and Induced Bipartite Subgraphs -- Stable Sets -- Traveling Salesman Problems -- Packing -- Scheduling -- Computational Biology Problems. 
516 |a text file PDF 
520 |a This book provides a handy, unified introduction to the theory of compact extended formulations of exponential-size integer linear programming (ILP) models. Compact extended formulations are equally powerful polynomial-sized models whose solutions do not require the implementation of separation and pricing procedures. The book is written in a general, didactic form, first developing the background theoretical concepts (polyhedra, projections, linear and integer programming) and then delving into the various techniques for compact extended reformulations. The techniques are illustrated through a wealth of examples touching on many application areas, such as classical combinatorial optimization, network design, timetabling, scheduling, routing, computational biology and bioinformatics. The book is intended for graduate or PhD students - either as an advanced course on selected topics or within a more general course on ILP and mathematical programming - as well as for practitioners and software engineers in industry exploring techniques for developing optimization models for their specific problems. 
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650 0 |a Decision making. 
650 0 |a Management science. 
650 0 |a Mathematical models. 
650 0 |a Data mining. 
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