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| 001 | ocn883892138 | ||
| 003 | OCoLC | ||
| 005 | 20240523125537.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 140718s2014 enk ob 001 0 eng d | ||
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_a(OCoLC)883892138 _z(OCoLC)894731734 _z(OCoLC)961545597 _z(OCoLC)992921557 _z(OCoLC)1055391424 _z(OCoLC)1081223861 _z(OCoLC)1228560238 |
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| 050 | 4 | _aT57.7 | |
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_aMAT _x003000 _2bisacsh |
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_aMAT _x029000 _2bisacsh |
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| 082 | 0 | 4 |
_a519.7 _222 |
| 049 | _aMAIN | ||
| 245 | 0 | 0 |
_aMathematical programming solver based on local search / _cFr�ed�eric Gardi [and others]. |
| 260 |
_aLondon : _bISTE Ltd. ; _aHoboken : _bWiley, _c�2014. |
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| 300 | _a1 online resource | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 1 |
_aFocus Computer Engineering Series, _x2051-249X |
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| 504 | _aIncludes bibliographical references and index. | ||
| 588 | 0 | _aPrint version record. | |
| 520 | _aThis 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. | ||
| 505 | 0 | _aCover; 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. | |
| 505 | 8 | _a1.3. 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. | |
| 505 | 8 | _a2.5.4. 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 |
_aJohn Wiley and Sons _bWiley Online Library: Complete oBooks |
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| 650 | 0 | _aMathematical optimization. | |
| 650 | 6 | _aOptimisation math�ematique. | |
| 650 | 7 |
_aMATHEMATICS _xApplied. _2bisacsh |
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| 650 | 7 |
_aMATHEMATICS _xProbability & Statistics _xGeneral. _2bisacsh |
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| 650 | 7 |
_aMathematical optimization _2fast |
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| 700 | 1 | _aGardi, Fr�ed�eric. | |
| 758 |
_ihas work: _aMathematical programming solver based on local search (Text) _1https://id.oclc.org/worldcat/entity/E39PCFTfKrYbv4XvJXfjmbgJwy _4https://id.oclc.org/worldcat/ontology/hasWork |
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| 776 | 0 | 8 |
_iPrint version: _tMathematical programming solver based on local search. _dLondon : ISTE Ltd. ; Hoboken : Wiley, �2014 _z9781118966464 |
| 830 | 0 | _aFocus series in computer engineering. | |
| 856 | 4 | 0 | _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781118966464 |
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