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Algorithms and complexity : 9th International Conference, CIAC 2015, Paris, France, May 20-22, 2015 ; proceedings (2015)

Paschos, Vangelis Th. ; CIAC 9. 2015 Paris

Cham [u.a.] :Springer,

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almahu_BV042539713

Format: XV, 430 S. : , graph. Darst.

ISBN: 978-3-319-18172-1

Series Statement: Lecture notes in computer science 9079

Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-319-18173-8

Language: English

Subjects: Computer Science

RVK:

SS 4800

Keywords: Algorithmus ; Komplexitätstheorie ; Konferenzschrift ; Konferenzschrift

Author information: Paschos, Vangelis Th.

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Combinatorial optimization and theoretical computer science : interfaces and perspectives ; 30th anniversary of the LAMSADE (2008)

Paschos, Vangelis Th.

London :ISTE, | Hoboken, NJ :Wiley.

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almahu_BV035115820

Format: 515 S. : , graph. Darst.

ISBN: 978-1-84821-021-9

Note: Includes index.

Language: English

Subjects: Computer Science , Mathematics

RVK:

ST 130

RVK:

SK 890

Keywords: Theoretische Informatik ; Kombinatorische Optimierung ; Aufsatzsammlung ; Aufsatzsammlung

URL: Table of contents only

URL: Contributor biographical information

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URL: http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016783559&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA

URL: http://www.loc.gov/catdir/toc/ecip0720/2007024974.html

URL: http://www.loc.gov/catdir/enhancements/fy0810/2007024974-b.html

URL: http://www.loc.gov/catdir/enhancements/fy0810/2007024974-d.html

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Combinatorial Optimization : Second International Symposium, ISCO 2012, Athens, Greece, April 19-21, 2012, Revised Selected Papers (2012)

Mahjoub, A. Ridha. [editor.] ; Markakis, Vangelis. [editor.] ; Milis, Ioannis. [editor.] ; [et al.]

Berlin, Heidelberg :Springer Berlin Heidelberg :

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almahu_9947364493502882

Format: XIV, 476 p. 63 illus. , online resource.

ISBN: 9783642321474

Series Statement: Lecture Notes in Computer Science, 7422

Content: This book constitutes the thoroughly refereed post-conference proceedings of the Second International Symposium on Combinatorial Optimization, ISCO 2012, held in Athens, Greece, in April 2012. The 37 revised full papers presented together with 4 invited talks were carefully reviewed and selected from 94 regular and 30 short submissions. They present original research on all aspects of combinatorial optimization, ranging from mathematical foundations and theory of algorithms to computational studies and practical applications.

Note: Structure Theorems for Optimum Hyperpaths in Directed Hypergraphs -- Branch-and-Price Guided -- The New Faces of Combinatorial Optimization -- Models and Algorithms for the Train Unit Assignment Problem -- The Minimum Stabbing Triangulation Problem: IP Models and Computational Evaluation -- Using Symmetry to Optimize over the Sherali-Adams Relaxation -- A Second-Order Cone Programming Approximation to Joint Chance-Constrained Linear Programs -- Semidefinite Relaxations for Mixed 0-1 Second-Order Cone Program -- The Non-Disjoint m-Ring-Star Problem : Polyhedral Results and SDH/SONET Network Design.-The Uncapacitated Asymmetric Traveling Salesman Problem with Multiple Stacks -- Polyhedral Analysis and Branch-and-Cut for the Structural Analysis Problem -- Extended Formulations, Nonnegative Factorizations, and Randomized Communication Protocols -- An Algebraic Approach to Symmetric Extended Formulations -- Dual Consistent Systems of Linear Inequalities and Cardinality Constrained Polytopes -- Minimum Ratio Cover of Matrix Columns by Extreme Rays of Its Induced Cone.-The Uncapacitated Asymmetric Traveling Salesman Problem with Multiple Stacks -- Polyhedral Analysis and Branch-and-Cut for the Structural Analysis Problem -- Extended Formulations, Nonnegative Factorizations, and Randomized Communication -- An Algebraic Approach to Symmetric Extended.-On the Hop Constrained Steiner Tree Problem with Multiple Root.-Structure Theorems for Optimum Hyperpaths in Directed Hypergraphs -- A Second-Order Cone Programming Approximation to Joint Chance-Constrained Linear Programs.-Extended Formulations, Nonnegative Factorizations, and Randomized Communication -- An Algebraic Approach to Symmetric Extended.-Gap Inequalities for the Max-Cut Problem: A Cutting-Plane Algorithm.

In: Springer eBooks

Additional Edition: Printed edition: ISBN 9783642321467

Language: English

Subjects: Computer Science

RVK:

SS 4800

Keywords: Konferenzschrift ; Konferenzschrift

DOI: 10.1007/978-3-642-32147-4

URL: http://dx.doi.org/10.1007/978-3-642-32147-4

URL: Volltext (lizenzpflichtig)

URL: Cover

URL: Inhaltstext

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Paradigms of Combinatorial Optimization : Problems and New Approaches. (2013)

Paschos, Vangelis Th.

London :Wiley,

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almafu_9959328279202883

Format: 1 online resource (722 pages)

ISBN: 9781118600276 , 1118600274 , 9781118600207 , 1118600207 , 9781118600184 , 1118600185 , 1322060878 , 9781322060873 , 9781119015192 , 1119015197

Series Statement: ISTE

Content: 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. "Paradigms of Combinatorial Optimization" is divided in two parts: Paradigmatic Problems, that handles several famous combinatorial optimization probl.

Note: Cover; Paradigms of Combinatorial Optimization; Title Page; Copyright Page; Table of Contents; Preface; PART I. PARADIGMATIC PROBLEMS; Chapter 1. Optimal Satisfiability; 1.1. Introduction; 1.2. Preliminaries; 1.2.1. Constraint satisfaction problems: decision and optimization versions; 1.2.2. Constraint types; 1.3. Complexity of decision problems; 1.4. Complexity and approximation of optimization problems; 1.4.1. Maximization problems; 1.4.2. Minimization problems; 1.5. Particular instances of constraint satisfaction problems; 1.5.1. Planar instances; 1.5.2. Dense instances. , Chapter 3. Location Problems3.1. Introduction; 3.1.1. Weber's problem; 3.1.2. A classification; 3.2. Continuous problems; 3.2.1. Complete covering; 3.2.2. Maximal covering; 3.2.3. Empty covering; 3.2.4. Bicriteria models; 3.2.5. Covering with multiple resources; 3.3. Discrete problems; 3.3.1. p-Center; 3.3.2. p-Dispersion; 3.3.3. p-Median; 3.3.4. Hub; 3.3.5. p-Maxisum; 3.4. On-line problems; 3.5. The quadratic assignment problem; 3.5.1. Definitions and formulations of the problem; 3.5.2. Complexity; 3.5.3. Relaxations and lower bounds; 3.6. Conclusion; 3.7. Bibliography. , 5.3.3. Bin packing: one-phase level heuristics5.3.4. Bin packing: one-phase non-level heuristics; 5.3.5. Metaheuristics; 5.3.6. Approximation algorithms; 5.4. Lower bounds; 5.4.1. Lower bounds for level packing; 5.5. Exact algorithms; 5.6. Acknowledgements; 5.7. Bibliography; Chapter 6. The Maximum Cut Problem; 6.1. Introduction; 6.2. Complexity and polynomial cases; 6.3. Applications; 6.3.1. Spin glass models; 6.3.2. Unconstrained 0-1 quadratic programming; 6.3.3. The via minimization problem; 6.4. The cut polytope; 6.4.1. Valid inequalities and separation; 6.4.2. Branch-and-cut algorithms.

Language: English

Keywords: Electronic books. ; Electronic books. ; Electronic books.

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781118600207

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Concepts of combinatorial optimization / (2010)

Paschos, Vangelis Th.

London :Wiley-ISTE,

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almafu_9959328963702883

Format: 1 online resource

ISBN: 9781118600191 , 1118600193 , 9781118600245 , 111860024X , 9781118600238 , 1118600231

Note: v. 1. Concepts of combinatorial optimization.

Additional Edition: Print version: Paschos, Vangelis Th. Concepts of combinatorial optimization. London : Wiley-ISTE, 2010 ISBN 9781848211476

Language: English

Keywords: Electronic books. ; Electronic books. ; Electronic books.

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781118600245

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Probabilistic combinatorial optimization on graphs / (2006)

Murat, Cecile. ; Paschos, Vangelis Th.

London ; : ISTE,

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Format: 1 online resource (267 pages) : , illustrations

ISBN: 9780470612507 , 0470612509 , 9781847045836 , 1847045839 , 1280510617 , 9781280510618

Content: This title provides a comprehensive survey over the subject of probabilistic combinatorial optimization, discussing probabilistic versions of some of the most paradigmatic combinatorial problems on graphs, such as the maximum independent set, the minimum vertex covering, the longest path and the minimum coloring. Detailed discussion is given to a priori optimization, which is adopted as the main working hypothesis: starting from an a priori solution of a super instance of a problem, where any datum is present with a certain probability, this hypothesis consists of creating modifications in or.

Note: Preliminaries; Contents; Chapter 1. A Short Insight into Probabilistic Combinatorial Optimization; Chapter 2. The Probabilistic Maximum Independent Set; Chapter 3. The Probabilistic Minimum Vertex Cover; Chapter 4. The Probabilistic Longest Path; Chapter 5. Probabilistic Minimum Coloring; Chapter 6. Classification of Probabilistic Graph-problems; Chapter 7. A Compendium of Probabilistic NPO Problems on Graphs; Appendix A. Mathematical Preliminaries; Appendix B. Elements of the Complexity and the Approximation Theory; Bibliography; Index.

Additional Edition: Print version: Murat, Cecile. Probabilistic combinatorial optimization on graphs. London ; Newport Beach, CA : ISTE, 2006 ISBN 1905209339

Additional Edition: ISBN 9781905209330

Language: English

Keywords: Electronic books. ; Electronic books. ; Electronic books.

DOI: 10.1002/9780470612507

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9780470612507

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Applications of combinatorial optimization / (2014)

Paschos, Vangelis Th.

London ; : Wiley,

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almafu_9959328661502883

Format: 1 online resource (449 pages)

Edition: 2nd ed.

ISBN: 9781119005384 , 1119005388 , 9781119015222 , 1119015227

Series Statement: ISTE

Content: 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 aim 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. Concepts of Combinatorial Optimization, is divided into three parts:- On the complexity of combinatorial optimization problems, presenting basics abo.

Note: 4.4.1. A linear programming model for medium-term planning. , Cover; Title Page; Copyright; 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 generation. , 1.4.3. Case of one single resource: the bucket method1.4.4. Case of many resources: reduction of the resource space; 1.4.4.1. Reduction principle; 1.4.4.2. Approach based on the Lagrangian relaxation; 1.4.4.3. Approach based on the surrogate relaxation; 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; 2.2.5.1. Static allocation; 2.2.5.2. Dynamic allocation; 2.2.5.3. With or without pre-emption. , 2.2.5.4. Task duplication2.2.6. Allocation/scheduling; 2.2.7. Modeling; 2.2.7.1. Modeling costs; 2.2.7.2. Constraints; 2.2.7.3. Objectives of the allocation; 2.2.7.3.1. Minimizing the execution duration; 2.2.7.3.2. Minimizing the global execution and communication cost; 2.2.7.3.3. Load balancing; 2.3. Review of the main works; 2.3.1. Polynomial cases; 2.3.1.1. Two-processor cases; 2.3.1.2. Tree case; 2.3.1.3. Other structures; 2.3.1.4. Restrictions on the processors or the tasks; 2.3.1.5. Minmax objective; 2.3.2. Approximability; 2.3.3. Approximate solution; 2.3.3.1. Heterogenous processors. , 2.3.3.2. Homogenous processors2.3.4. Exact solution; 2.3.5. Independent tasks case; 2.4. A little-studied model; 2.4.1. Model; 2.4.2. A heuristic based on graphs; 2.4.2.1. Transformation of the problem; 2.4.2.2. Modeling; 2.4.2.3. Description of the heuristic; 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 results; 3.3.1. 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.

Language: English

Keywords: Electronic books. ; Electronic books. ; Electronic books.

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119005384

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Concepts of combinatorial optimization / (2014)

Paschos, Vangelis Th.

Hoboken :Wiley,

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almafu_9959328662102883

Format: 1 online resource (409 pages)

Edition: 2nd ed.

ISBN: 9781119005216 , 1119005213 , 9781119015185 , 1119015189

Series Statement: ISTE

Content: 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 aim 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. Concepts of Combinatorial Optimization, is divided into three parts:- On the complexity of combinatorial optimization problems, presenting basics abo.

Note: Chapter 5: Mixed Integer Linear Programming Models forCombinatorial Optimization Problems. , Cover; Title Page; Copyright; Contents; Preface; PART I: Complexity of CombinatorialOptimization Problems; Chapter 1: Basic Concepts in Algorithmsand Complexity Theory; 1.1. Algorithmic complexity; 1.2. Problem complexity; 1.3. The classes P, NP and NPO; 1.4. Karp and Turing reductions; 1.5. NP-completeness; 1.6. Two examples of NP-complete problems; 1.6.1. MIN VERTEX COVER; 1.6.2. MAX STABLE; 1.7. A few words on strong and weak NP-completeness; 1.8. A few other well-known complexity classes; 1.9. Bibliography; Chapter 2: Randomized Complexity; 2.1. Deterministic and probabilistic algorithms. , 2.1.1. Complexity of a Las Vegas algorithm2.1.2. Probabilistic complexity of a problem; 2.2. Lower bound technique; 2.2.1. Definitions and notations; 2.2.2. Minimax theorem; 2.2.3. The Loomis lemma and the Yao principle; 2.3. Elementary intersection problem; 2.3.1. Upper bound; 2.3.2. Lower bound; 2.3.3. Probabilistic complexity; 2.4. Conclusion; 2.5. Bibliography; PART II: Classical Solution Methods; Chapter 3: Branch-and-Bound Methods; 3.1. Introduction; 3.2. Branch-and-bound method principles; 3.2.1. Principle of separation; 3.2.2. Pruning principles; 3.2.2.1. Bound. , 3.2.2.2. Evaluation function3.2.2.3. Use of the bound and of the evaluation function for pruning; 3.2.2.4. Other pruning principles; 3.2.2.5. Pruning order; 3.2.3. Developing the tree; 3.2.3.1. Description of development strategies; 3.2.3.2. Compared properties of the depth first and best first strategies; 3.3. A detailed example: the binary knapsack problem; 3.3.1. Calculating the initial bound; 3.3.2. First principle of separation; 3.3.3. Pruning without evaluation; 3.3.4. Evaluation; 3.3.5. Complete execution of the branch-and-bound method for finding only oneoptimal solution. , 3.3.6. First variant: finding all the optimal solutions3.3.7. Second variant: best first search strategy; 3.3.8. Third variant: second principle of separation; 3.4. Conclusion; 3.5. Bibliography; Chapter 4: Dynamic Programming; 4.1. Introduction; 4.2. A first example: crossing the bridge; 4.3. Formalization; 4.3.1. State space, decision set, transition function; 4.3.2. Feasible policies, comparison relationships and objectives; 4.4. Some other examples; 4.4.1. Stock management; 4.4.2. Shortest path bottleneck in a graph; 4.4.3. Knapsack problem; 4.5. Solution; 4.5.1. Forward procedure. , 4.5.2. Backward procedure4.5.3. Principles of optimality and monotonicity; 4.6. Solution of the examples; 4.6.1. Stock management; 4.6.2. Shortest path bottleneck; 4.6.3. Knapsack; 4.7. A few extensions; 4.7.1. Partial order and multicriteria optimization; 4.7.1.1. New formulation of the problem; 4.7.1.2. Solution; 4.7.1.3. Examples; 4.7.2. Dynamic programming with variables; 4.7.2.1. Sequential decision problems under uncertainty; 4.7.2.2. Solution; 4.7.2.3. Example; 4.7.3. Generalized dynamic programming; 4.8. Conclusion; 4.9. Bibliography; PART III: Elements from MathematicalProgramming.

Language: English

Keywords: Electronic books. ; Electronic books. ; Electronic books.

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119005216

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Paradigms of combinatorial optimization / (2014)

Paschos, Vangelis Th.

London :ISTE, Ltd. ;

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almafu_9959328662502883

Format: 1 online resource (815 pages)

Edition: 2nd ed.

ISBN: 9781119005353 , 1119005353 , 9781119015161 , 1119015162

Series Statement: ISTE

Content: 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 aim 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. Concepts of Combinatorial Optimization, is divided into three parts:- On the complexity of combinatorial optimization problems, presenting basics.

Note: 5.3.4. Bin packing: one-phase non-level heuristics. , 4.2. Games of no chance: the simple cases4.3. The case of complex no chance games; 4.3.1. Approximative evaluation; 4.3.2. Horizon effect; 4.3.3. [alpha]-[beta] pruning; 4.4. Quiescence search; 4.4.1. Other refinements of the MiniMax algorithm; 4.5. Case of games using chance; 4.6. Conclusion; 4.7. Bibliography; Chapter 5: Two-dimensional Bin Packing Problems; 5.1. Introduction; 5.2. Models; 5.2.1. ILP models for level packing; 5.3. Upper bounds; 5.3.1. Strip packing; 5.3.2. Bin packing: two-phase heuristics; 5.3.3. Bin packing: one-phase level heuristics. , Cover; Title Page; Copyright; Contents; Preface; PART I: Paradigmatic Problems; Chapter 1: Optimal Satisfiability; 1.1. Introduction; 1.2. Preliminaries; 1.2.1. Constraint satisfaction problems: decision and optimization versions; 1.2.2. Constraint types; 1.3. Complexity of decision problems; 1.4. Complexity and approximation of optimization problems; 1.4.1. Maximization problems; 1.4.2. Minimization problems; 1.5. Particular instances of constraint satisfaction problems; 1.5.1. Planar instances; 1.5.2. Dense instances; 1.5.3. Instances with a bounded number of occurrences. , 1.6. Satisfiability problems under global constraints1.7. Conclusion; 1.8. Bibliography; Chapter 2: Scheduling Problems; 2.1. Introduction; 2.2. New techniques for approximation; 2.2.1. Linear programming and scheduling; 2.2.1.1. Single machine problems; 2.2.1.2. Problems with m machines; 2.2.2. An approximation scheme for PCmax; 2.3. Constraints and scheduling; 2.3.1. The monomachine constraint; 2.3.2. The cumulative constraint; 2.3.3. Energetic reasoning; 2.4. Non-regular criteria; 2.4.1. PERT with convex costs; 2.4.1.1. The equality graph and its blocks; 2.4.1.2. Generic algorithm. , 2.4.1.3. Complexity of the generic algorithm2.4.2. Minimizing the early-tardy cost on one machine; 2.4.2.1. Special cases; 2.4.2.2. The lower bound; 2.4.2.3. The branch-and-bound algorithm; 2.4.2.4. Lower bounds in a node of the search tree; 2.4.2.5. Upper bound; 2.4.2.6. Branching rule; 2.4.2.7. Dominance rules; 2.4.2.8. Experimental results; 2.5. Bibliography; Chapter 3: Location Problems; 3.1. Introduction; 3.1.1. Weber's problem; 3.1.2. A classification; 3.2. Continuous problems; 3.2.1. Complete covering; 3.2.2. Maximal covering; 3.2.2.1. Fixed radius; 3.2.2.2. Variable radius. , 3.2.3. Empty covering3.2.4. Bicriteria models; 3.2.5. Covering with multiple resources; 3.3. Discrete problems; 3.3.1. p-Center; 3.3.2. p-Dispersion; 3.3.3. p-Median; 3.3.3.1. Fixed charge; 3.3.4. Hub; 3.3.5. p-Maxisum; 3.4. On-line problems; 3.5. The quadratic assignment problem; 3.5.1. Definitions and formulations of the problem; 3.5.2. Complexity; 3.5.3. Relaxations and lower bounds; 3.5.3.1. Linear relaxations; 3.5.3.2. Semi-definite relaxations; 3.5.3.3. Convex quadratic relaxations; 3.6. Conclusion; 3.7. Bibliography; Chapter 4: MiniMax Algorithms and Games; 4.1. Introduction.

Language: English

Keywords: Electronic books. ; Electronic books. ; Electronic books.

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119005353

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Applications of Combinatorial Optimization. (2013)

Paschos, Vangelis Th.

London :Wiley,

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almafu_9959328277802883

Format: 1 online resource (409 pages)

ISBN: 9781118600283 , 1118600282

Series Statement: ISTE

Content: 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.

Note: 5.5.1. Definitions and complexity. , 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 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.

Language: English

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