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|a Mathematical programming solver based on local search /
|c Frédéric Gardi [and others].
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260 |
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|a London :
|b ISTE Ltd. ;
|a Hoboken :
|b Wiley,
|c ©2014.
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|a 1 online resource
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
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1 |
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|a Focus Computer Engineering Series,
|x 2051-249X
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504 |
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|a Includes bibliographical references and index.
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|a Print version record.
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|a This book covers local search for combinatorial optimization and its extension to mixed-variable optimization. Although not yet understood from the theoretical point of view, local search is the paradigm of choice for tackling large-scale real-life optimization problems. Today's end-users demand interactivity with decision support systems. For optimization software, this means obtaining good-quality solutions quickly. Fast iterative improvement methods, like local search, are suited to satisfying such needs. Here the authors show local search in a new light, in particular presenting a new kin.
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|a Cover; Title Page; Copyright; Contents; Acknowledgments; Preface; Introduction; Chapter 1. Local Search: Methodology and Industrial Applications; 1.1. Our methodology: back to basics; 1.1.1. What are the needs in business and industry?; 1.1.2. The main ingredients of the recipe; 1.1.3. Enriching and enlarging neighborhoods; 1.1.4. High-performance software engineering; 1.2. Car sequencing for painting and assembly lines; 1.2.1. Search strategy and moves; 1.2.2. Enriching the moves and boosting their evaluation; 1.2.3. Experimental results and discussion.
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|a 1.3. Vehicle routing with inventory management1.3.1. State-of-the-art; 1.3.2. Search strategy and moves; 1.3.3. Incremental evaluation machinery; Chapter 2. Local Search for 0-1 Nonlinear Programming; 2.1. The LocalSolver project; 2.2. State-of-the-art; 2.3. Enriching modeling standards; 2.3.1. LocalSolver modeling formalism; 2.3.2. LocalSolver programming language; 2.4. The core algorithmic ideas; 2.4.1. Effective local search moves; 2.4.2. Incremental evaluation machinery; 2.5. Benchmarks; 2.5.1. Car sequencing; 2.5.2. Machine scheduling; 2.5.3. Quadratic assignment problem.
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|a 2.5.4. MIPLIB 2010Chapter 3. Toward an Optimization Solver Based on Neighborhood Search; 3.1. Using neighborhood search as global search strategy; 3.2. Extension to continuous and mixed optimization; 3.3. Separating the computation of solutions and bounds; 3.4. A new-generation, hybrid mathematical programming solver; Bibliography; Lists of Figures and Tables; Index.
|
590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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650 |
|
0 |
|a Mathematical optimization.
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650 |
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6 |
|a Optimisation mathématique.
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650 |
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7 |
|a MATHEMATICS
|x Applied.
|2 bisacsh
|
650 |
|
7 |
|a MATHEMATICS
|x Probability & Statistics
|x General.
|2 bisacsh
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650 |
|
7 |
|a Mathematical optimization
|2 fast
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700 |
1 |
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|a Gardi, Frédéric.
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758 |
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|i has work:
|a Mathematical programming solver based on local search (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCFTfKrYbv4XvJXfjmbgJwy
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
776 |
0 |
8 |
|i Print version:
|t Mathematical programming solver based on local search.
|d London : ISTE Ltd. ; Hoboken : Wiley, ©2014
|z 9781118966464
|
830 |
|
0 |
|a Focus series in computer engineering.
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856 |
4 |
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|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1734304
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