國立高雄大學圖資館 |

Language: English

Back

Handbook of metaheuristics

Gendreau, Michel.

Handbook of metaheuristics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Handbook of metaheuristicsedited by Michel Gendreau, Jean-Yves Potvin.
other author:	Gendreau, Michel.
Published:	Cham :Springer International Publishing :2019.
Description:	xx, 604 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Mathematical optimization
Online resource:	https://doi.org/10.1007/978-3-319-91086-4
ISBN:	9783319910864$q(electronic bk.)

Handbook of metaheuristics
Handbook of metaheuristics[electronic resource] /edited by Michel Gendreau, Jean-Yves Potvin. - 3rd ed. - Cham :Springer International Publishing :2019. - xx, 604 p. :ill., digital ;24 cm. - International series in operations research & management science,v.2720884-8289 ;. - International series in operations research & management science ;v. 140..

Chapter 1. Simulated Annealing: From Basics to Applications -- Chapter 2. Tabu Search -- Chapter 3. Variable Neighborhood Search -- Chapter 4. Large Neighborhood Search -- Chapter 5. Iterated Local Search: Framework and Applications -- Chapter 6. Greedy Randomized Adaptive Search Procedures: Advances and Extensions -- Chapter 7. Intelligent Multi-Start Methods -- Chapter 8. Next Generation Genetic Algorithms: A User's Guide and Tutorial -- Chapter 9. An Accelerated Introduction to Memetic Algorithms -- Chapter 10. Ant Colony Optimization: Overview and Recent Advances -- Chapter 11. Swarm Intelligence -- Chapter 12. Metaheuristic Hybrids -- Chapter 13. Parallel Metaheuristics and Cooperative Search -- Chapter 14. A Classification of Hyper-heuristic Approaches - Revisited -- Chapter 15. Reactive Search Optimization: Learning while Optimizing -- Chapter 16. Stochastic Search in Metaheuristics -- Chapter 17. Automated Design of Metaheuristic Algorithms -- Chapter 18. Computational Comparison of Metaheuristics.

The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book's chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular. Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.

ISBN: 9783319910864$q(electronic bk.)

Standard No.: 10.1007/978-3-319-91086-4doiSubjects--Topical Terms:

252884
Mathematical optimization

LC Class. No.: T57 / .H363 2019

Dewey Class. No.: 658.4034

Handbook of metaheuristics
LDR:03998nmm a2200361 a 4500 001 552005
003 DE-He213
005 20190516153446.0
006 m d
007 cr nn 008maaau
008 191105s2019 gw s 0 eng d
020 $a 9783319910864$q(electronic bk.)
020 $a 9783319910857$q(paper)
024 7 $a 10.1007/978-3-319-91086-4 $2 doi
035 $a 978-3-319-91086-4
040 $a GP $c GP
041 0 $a eng
050 4 $a T57 $b .H363 2019
072 7 $a KJT $2 bicssc
072 7 $a BUS049000 $2 bisacsh
072 7 $a KJT $2 thema
072 7 $a KJMD $2 thema
082 0 4 $a 658.4034 $2 23
090 $a T57 $b .H236 2019
245 0 0 $a Handbook of metaheuristics $h [electronic resource] / $c edited by Michel Gendreau, Jean-Yves Potvin.
250 $a 3rd ed.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xx, 604 p. : $b ill., digital ; $c 24 cm.
490 1 $a International series in operations research & management science, $x 0884-8289 ; $v v.272
505 0 $a Chapter 1. Simulated Annealing: From Basics to Applications -- Chapter 2. Tabu Search -- Chapter 3. Variable Neighborhood Search -- Chapter 4. Large Neighborhood Search -- Chapter 5. Iterated Local Search: Framework and Applications -- Chapter 6. Greedy Randomized Adaptive Search Procedures: Advances and Extensions -- Chapter 7. Intelligent Multi-Start Methods -- Chapter 8. Next Generation Genetic Algorithms: A User's Guide and Tutorial -- Chapter 9. An Accelerated Introduction to Memetic Algorithms -- Chapter 10. Ant Colony Optimization: Overview and Recent Advances -- Chapter 11. Swarm Intelligence -- Chapter 12. Metaheuristic Hybrids -- Chapter 13. Parallel Metaheuristics and Cooperative Search -- Chapter 14. A Classification of Hyper-heuristic Approaches - Revisited -- Chapter 15. Reactive Search Optimization: Learning while Optimizing -- Chapter 16. Stochastic Search in Metaheuristics -- Chapter 17. Automated Design of Metaheuristic Algorithms -- Chapter 18. Computational Comparison of Metaheuristics.
520 $a The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book's chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular. Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.
650 0 $a Mathematical optimization $3 252884
650 0 $a Operations research $3 216699
650 1 4 $a Operations Research/Decision Theory. $3 273963
650 2 4 $a Operations Research, Management Science. $3 511451
650 2 4 $a Math Applications in Computer Science. $3 273991
700 1 $a Gendreau, Michel. $3 491946
700 1 $a Potvin, Jean-Yves. $3 491947
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a International series in operations research & management science ; $v v. 140. $3 490892
856 4 0 $u https://doi.org/10.1007/978-3-319-91086-4
950 $a Business and Management (Springer-41169)