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dc.contributor.authorTaillard, Éric D.
dc.date.accessioned2022-11-18T14:20:22Z
dc.date.available2022-11-18T14:20:22Z
dc.date.issued2023
dc.identifierONIX_20221118_9783031137143_38
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/59365
dc.description.abstractThis 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.
dc.languageEnglish
dc.relation.ispartofseriesGraduate Texts in Operations Research
dc.subject.classificationthema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJT Operational researchen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PB Mathematics::PBU Optimizationen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysisen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PD Science: general issues::PDE Maths for scientistsen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligenceen_US
dc.subject.otherAlgorithms
dc.subject.otherHeuristics
dc.subject.otherTravelling Salesman
dc.subject.otherLocal Search
dc.subject.otherMetaheuristics
dc.subject.otherCombinatorial Optimization
dc.subject.otherArtificial Intelligence
dc.titleDesign of Heuristic Algorithms for Hard Optimization
dc.title.alternativeWith Python Codes for the Travelling Salesman Problem
dc.typebook
oapen.identifier.doi10.1007/978-3-031-13714-3
oapen.relation.isPublishedBy6c6992af-b843-4f46-859c-f6e9998e40d5
oapen.relation.isFundedBy07f61e34-5b96-49f0-9860-c87dd8228f26
oapen.relation.isbn9783031137143
oapen.collectionSwiss National Science Foundation (SNF)
oapen.imprintSpringer International Publishing
oapen.pages287
oapen.place.publicationCham
oapen.grant.number[...]


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