Iste : (Record no. 85343)

MARC details
000 -LEADER
fixed length control field 12248nam a22005293i 4500
001 - CONTROL NUMBER
control field EBC1765110
003 - CONTROL NUMBER IDENTIFIER
control field MiAaPQ
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20191126115314.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m o d |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cnu||||||||
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 191125s2014 xx o ||||0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781119015161
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781119005353
035 ## - SYSTEM CONTROL NUMBER
System control number (MiAaPQ)EBC1765110
035 ## - SYSTEM CONTROL NUMBER
System control number (Au-PeEL)EBL1765110
035 ## - SYSTEM CONTROL NUMBER
System control number (CaPaEBR)ebr10907543
035 ## - SYSTEM CONTROL NUMBER
System control number (CaONFJC)MIL637338
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)887507243
040 ## - CATALOGING SOURCE
Original cataloging agency MiAaPQ
Language of cataloging eng
Description conventions rda
-- pn
Transcribing agency MiAaPQ
Modifying agency MiAaPQ
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA402.5 -- .P373 2014eb
082 0# - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.64
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Paschos, Vangelis.
9 (RLIN) 91955
245 10 - TITLE STATEMENT
Title Iste :
Remainder of title Paradigms of Combinatorial Optimization : Problems and New Approaches (2nd Edition).
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Somerset :
Name of producer, publisher, distributor, manufacturer John Wiley & Sons, Incorporated,
Date of production, publication, distribution, manufacture, or copyright notice 2014.
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice ©2014.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (815 pages)
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
490 1# - SERIES STATEMENT
Series statement ISTE
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 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 constraints -- 1.7. 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 P||Cmax -- 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 algorithm -- 2.4.2. 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.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 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 -- 3.3.3.1. 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 -- 4.2. Games of no chance: the simple cases -- 4.3. The case of complex no chance games -- 4.3.1. Approximative evaluation -- 4.3.2. Horizon effect -- 4.3.3. α-β 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 -- 5.3.4. 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 -- 6.4.3. The cut polyhedron.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 6.5. Semi-definite programming (SDP) and the maximum cut problem -- 6.5.1. Semi-definite formulation of the MAX-CUT problem -- 6.5.2. Quality of the semi-definite formulation -- 6.5.3. Existing works in the literature -- 6.6. The cut cone and applications -- 6.6.1. The cut cone -- 6.6.2. Relationship to the cut polytope -- 6.6.3. The semi-metric cone -- 6.6.4. Applications to the multiflow problem -- 6.7. Approximation methods -- 6.7.1. Methods with performance guarantees -- 6.7.2. Methods with no guarantees -- 6.8. Related problems -- 6.8.1. Unconstrained 0-1 quadratic programming -- 6.8.2. The maximum even (odd) cut problem -- 6.8.3. The equipartition problem -- 6.8.4. Other problems -- 6.9. Conclusion -- 6.10. Bibliography -- Chapter 7: The Traveling Salesman Problem and its Variations -- 7.1. Introduction -- 7.2. Elementary properties and various subproblems -- 7.2.1. Elementary properties -- 7.2.2. Various subproblems -- 7.3. Exact solving algorithms -- 7.3.1. A dynamic programming algorithm -- 7.3.2. A branch-and-bound algorithm -- 7.4. Approximation algorithm for max TSP -- 7.4.1. An algorithm based on 2-matching -- 7.4.2. Algorithm mixing 2-matching and matching -- 7.5. Approximation algorithm for min TSP -- 7.5.1. Algorithm based on the spanning tree and matching -- 7.5.2. Local search algorithm -- 7.6. Constructive algorithms -- 7.6.1. Nearest neighbor algorithm -- 7.6.1.1. The general case -- 7.6.1.2. The metric case -- 7.6.2. Nearest insertion algorithm -- 7.7. Conclusion -- 7.8. Bibliography -- Chapter 8: 0-1 Knapsack Problems -- 8.1. General solution principle -- 8.2. Relaxation -- 8.3. Heuristic -- 8.4. Variable fixing -- 8.5. Dynamic programming -- 8.5.1. General principle -- 8.5.2. Managing feasible combinations of objects -- 8.6. Solution search by hybridization of branch-and-bound and dynamic programming.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 8.6.1. Principle of hybridization -- 8.6.2. Illustration of hybridization -- 8.7. Conclusion -- 8.8. Bibliography -- Chapter 9: Integer Quadratic Knapsack Problems -- 9.1. Introduction -- 9.1.1. Problem formulation -- 9.1.2. Significance of the problem -- 9.1.2.1. A task assignment problem -- 9.1.2.2. Portfolio management -- 9.2. Solution methods -- 9.2.1. The convex separable problem -- 9.2.1.1. Solving the continuous relaxation -- 9.2.1.2. Calculating a "good" quality bound -- 9.2.2. The non-convex separable problem -- 9.2.3. The convex non-separable problem -- 9.2.4. The non-convex non-separable problem -- 9.2.4.1. Special case: the 0-1 variable quadratic knapsack problem -- 9.3. Numerical experiments -- 9.3.1. The convex and separable integer quadratic knapsack problem -- 9.3.2. The convex and separable integer quadratic multi-knapsack problem -- 9.4. Conclusion -- 9.5. Bibliography -- Chapter 10: Graph Coloring Problems -- 10.1. Basic notions of colorings -- 10.2. Complexity of coloring -- 10.3. Sequential methods of coloring -- 10.4. An exact coloring algorithm -- 10.5. Tabu search -- 10.6. Perfect graphs -- 10.7. Chromatic scheduling -- 10.8. Interval coloring -- 10.9. T-colorings -- 10.10. List colorings -- 10.11. Coloring with cardinality constraints -- 10.12. Other extensions -- 10.13. Edge coloring -- 10.13.1. f-Coloring of edge -- 10.13.2. [g, f]-Colorings of edges -- 10.13.3. A model of hypergraph coloring -- 10.14. Conclusion -- 10.15. Bibliography -- PART II: New Approaches -- Chapter 11: Polynomial Approximation -- 11.1. What is polynomial approximation? -- 11.1.1. Efficiently solving a difficult problem -- 11.1.2. Approximation measures -- 11.2. Some first examples of analysis: constant approximation ratios -- 11.2.1. An example of classical approximation: the metric traveling salesman.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 11.2.2. Examples of the differential ratio case -- 11.2.2.1. Bin packing -- 11.2.2.2. Minimum graph coloring -- 11.2.2.3. Polynomially bounded traveling salesman -- 11.3. Approximation schemes -- 11.3.1. Non-complete schemes -- 11.3.1.1. A scheduling problem with p processors for the classical ratio -- 11.3.1.2. The Euclidean traveling salesman problem -- 11.3.1.2.1. Phase 1 -- 11.3.1.2.2. Phase 2 -- 11.3.1.2.3. Phase 3 -- 11.3.1.3. An example in the case of the differential ratio: return to BIN PACKING -- 11.3.2. Complete approximation schemes - example of the Boolean knapsack -- 11.3.2.1. A great classic: the positive case for the classical ratio -- 11.3.2.2. A generalization: using the differential ratio -- 11.4. Analyses depending on the instance -- 11.4.1. Set covering and classical ratios -- 11.4.2. Set covering and differential ratios -- 11.4.3. The maximum stable set problem -- 11.5. Conclusion: methods and issues of approximation -- 11.5.1. The types of algorithms: a few great classics -- 11.5.2. Approximation classes: structuring the class NPO -- 11.5.3. Reductions in approximation -- 11.5.4. Issues -- 11.6. Bibliography -- Chapter 12: Approximation Preserving Reductions -- 12.1. Introduction -- 12.2. Strict and continuous reductions -- 12.2.1. Strict reductions -- 12.2.2. Continuous reduction -- 12.3. AP-reduction and completeness in the classes NPO and APX -- 12.3.1. Completeness in NPO -- 12.3.2. Completeness in APX -- 12.3.3. Using completeness to derive negative results -- 12.4. L-reduction and completeness in the classes Max-SNP and APX -- 12.4.1. The L-reduction and the class Max-SNP -- 12.4.2. Examples of L-reductions -- 12.4.2.1. MAX 2SAT and MIN 2SAT -- 12.4.2.2. MAX 3SAT and MAX 2SAT -- 12.4.2.3. MAX 2SAT and MAX ≠ 3SAT -- 12.4.3. Completeness in Max-SNP and APX -- 12.5. Affine reduction -- 12.6. A few words on GAP-reduction.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 12.7. History and comment.
520 ## - SUMMARY, ETC.
Summary, etc. 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 about worst-case and randomized complexity; - Classical solution methods, presenting the two most-known methods for solving hard combinatorial optimization problems, that are Branch-and-Bound and Dynamic Programming; - Elements from mathematical programming, presenting fundamentals from mathematical programming based methods that are in the heart of Operations Research since the origins of this field.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Description based on publisher supplied metadata and other sources.
590 ## - LOCAL NOTE (RLIN)
Local note Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2019. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Combinatorial optimization.;Programming (Mathematics).
9 (RLIN) 91956
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
9 (RLIN) 91957
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
Main entry heading Paschos, Vangelis
Title Iste : Paradigms of Combinatorial Optimization : Problems and New Approaches (2nd Edition)
Place, publisher, and date of publication Somerset : John Wiley & Sons, Incorporated,c2014
International Standard Book Number 9781119005353
797 2# - LOCAL ADDED ENTRY--CORPORATE NAME (RLIN)
Corporate name or jurisdiction name as entry element ProQuest (Firm)
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title ISTE
9 (RLIN) 91958
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://ebookcentral.proquest.com/lib/thebc/detail.action?docID=1765110">https://ebookcentral.proquest.com/lib/thebc/detail.action?docID=1765110</a>
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