000			03271nam a22003735i 4500
999			_c238240 _d238240
001			238240
003			ES-VaUE
005			20240523132732.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			221029s2023 sz | s |||| 0|eng d
020			_a9783031137143
024	7		_a10.1007/978-3-031-13714-3 _2doi
040			_aES-VaUEC _bspa _cES-VaUEC _dES-VaUE
050		4	_aT57.6 _b2023 EB
100	1		_aTaillard, Éric D. _eautor _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aDesign of Heuristic Algorithms for Hard Optimization : _bWith Python Codes for the Travelling Salesman Problem _cby Éric D Taillard
250			_a1st ed 2023
264		1	_aCham _c2023 _bSpringer International Publishing
300	0	0	_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aGraduate Texts in Operations Research _x2662-6020
505	0		_aPart I: Combinatorial Optimization, Complexity Theory and Problem Modelling -- 1. Elements of Graphs and Complexity Theory -- 2. A Short List of Combinatorial Optimization Problems -- 3. Problem Modelling -- Part II: Basic Heuristic Techniques -- 4. Constructive Methods -- 5. Local Search -- 6. Decomposition Methods -- Part III: Popular Metaheuristics -- 7. Randomized Methods -- 8. Construction Learning -- 9. Local Search Learning -- 10. Population Management -- 11. Heuristics Design -- 12. Codes.
520			_aThis open access book demonstrates all the steps required to design heuristic algorithms for difficult optimization. The classic problem of the travelling salesman is used as a common thread to illustrate all the techniques discussed. This problem is ideal for introducing readers to the subject because it is very intuitive and its solutions can be graphically represented. The book features a wealth of illustrations that allow the concepts to be understood at a glance. The book approaches the main metaheuristics from a new angle, deconstructing them into a few key concepts presented in separate chapters: construction, improvement, decomposition, randomization and learning methods. Each metaheuristic can then be presented in simplified form as a combination of these concepts. This approach avoids giving the impression that metaheuristics is a non-formal discipline, a kind of cloud sculpture. Moreover, it provides concrete applications of the travelling salesman problem, which illustrate in just a few lines of code how to design a new heuristic and remove all ambiguities left by a general framework. Two chapters reviewing the basics of combinatorial optimization and complexity theory make the book self-contained. As such, even readers with a very limited background in the field will be able to follow all the content.
988			_aSpringer_Business_2023
650		7	_2embne _aTecnología _97860
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-13714-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
998			_db