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1. |
Record Nr. |
UNINA9910787902503321 |
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Autore |
Shirer William L. |
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Titolo |
Journal de Berlin : 1934-1941 : chronique d'un correspondant étranger / / William L. Shirer |
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Pubbl/distr/stampa |
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Québec, [Canada] : , : Les Presses de l'Université Laval, , 2009 |
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©2009 |
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ISBN |
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1-4416-2918-1 |
1-4593-3745-X |
2-7637-0895-1 |
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Descrizione fisica |
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1 texte électronique (669 p.) : numérique, fichier PDF |
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Disciplina |
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Soggetti |
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World War, 1939-1945 - Germany |
World War, 1939-1945 |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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2. |
Record Nr. |
UNINA9910809344503321 |
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Titolo |
Applications of combinatorial optimization / / edited by Vangelis Th. Paschos |
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Pubbl/distr/stampa |
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London, : ISTE |
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Hoboken, N.J., : Wiley, 2010 |
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ISBN |
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9781118600283 |
1118600282 |
9781118600344 |
1118600347 |
9781118600115 |
1118600118 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (409 p.) |
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Collana |
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Combinatorial optimization ; ; v. 3 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Combinatorial optimization |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di contenuto |
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Cover; Applications of Combinatorial Optimization; Title Page; Copyright Page; Table of Contents; Preface; Chapter 1. Airline Crew Pairing Optimization; 1.1. Introduction; 1.2. Definition of the problem; 1.2.1. Constructing subnetworks; 1.2.2. Pairing costs; 1.2.3. Model; 1.2.4. Case without resource constraints; 1.3. Solution approaches; 1.3.1. Decomposition principles; 1.3.2. Column generation, master problem and subproblem; 1.3.3. Branching methods for finding integer solutions; 1.4. Solving the subproblem for column generation; 1.4.1. Mathematical formulation |
1.4.2. General principle of effective label generation1.4.3. Case of one single resource: the bucket method; 1.4.4. Case of many resources: reduction of the resource space; 1.5. Conclusion; 1.6. Bibliography; Chapter 2. The Task Allocation Problem; 2.1. Presentation; 2.2. Definitions and modeling; 2.2.1. Definitions; 2.2.2. The processors; 2.2.3. Communications; 2.2.4. Tasks; 2.2.5. Allocation types; 2.2.6. Allocation/scheduling; 2.2.7. Modeling; 2.3. Review of the main works; 2.3.1. Polynomial cases; 2.3.2. Approximability; 2.3.3. Approximate |
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solution; 2.3.4. Exact solution |
2.3.5. Independent tasks case2.4. A little-studied model; 2.4.1. Model; 2.4.2. A heuristic based on graphs; 2.5. Conclusion; 2.6. Bibliography; Chapter 3. A Comparison of Some Valid Inequality Generation Methods for General 0-1 Problems; 3.1. Introduction; 3.2. Presentation of the various techniques tested; 3.2.1. Exact separation with respect to a mixed relaxation; 3.2.2. Approximate separation using a heuristic; 3.2.3. Restriction + separation + relaxed lifting (RSRL); 3.2.4. Disjunctive programming and the lift and project procedure; 3.2.5. Reformulation-linearization technique (RLT) |
3.3. Computational results3.3.1. Presentation of test problems; 3.3.2. Presentation of the results; 3.3.3. Discussion of the computational results; 3.4. Bibliography; Chapter 4. Production Planning; 4.1. Introduction; 4.2. Hierarchical planning; 4.3. Strategic planning and productive system design; 4.3.1. Group technology; 4.3.2. Locating equipment; 4.4. Tactical planning and inventory management; 4.4.1. A linear programming model for medium-term planning; 4.4.2. Inventory management; 4.4.3. Wagner and Whitin model; 4.4.4. The economic order quantity model (EOQ) |
4.4.5. The EOQ model with joint replenishments4.5. Operations planning and scheduling; 4.5.1. Tooling; 4.5.2. Robotic cells; 4.6. Conclusion and perspectives; 4.7. Bibliography; Chapter 5. Operations Research and Goods Transportation; 5.1. Introduction; 5.2. Goods transport systems; 5.3. Systems design; 5.3.1. Location with balancing requirements; 5.3.2. Multiproduct production-distribution; 5.3.3. Hub location; 5.4. Long-distance transport; 5.4.1. Service network design; 5.4.2. Static formulations; 5.4.3. Dynamic formulations; 5.4.4. Fleet management; 5.5. Vehicle routing problems |
5.5.1. Definitions and complexity |
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Sommario/riassunto |
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Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aims to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. "Applications of Combinatorial Optimization" is presenting a certain number among the most common and well-known applications of Combinatorial Optimization. |
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