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oapen-20.500.12657-593652022-11-19T03:41:51Z Design of Heuristic Algorithms for Hard Optimization Taillard, Éric D. Algorithms Heuristics Travelling Salesman Local Search Metaheuristics Combinatorial Optimization Artificial Intelligence bic Book Industry Communication::K Economics, finance, business & management::KJ Business & management::KJT Operational research bic Book Industry Communication::P Mathematics & science::PB Mathematics::PBU Optimization bic Book Industry Communication::P Mathematics & science::PB Mathematics::PBK Calculus & mathematical analysis::PBKS Numerical analysis bic Book Industry Communication::P Mathematics & science::PD Science: general issues::PDE Maths for scientists bic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence This 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. 2022-11-18T14:20:22Z 2022-11-18T14:20:22Z 2023 book ONIX_20221118_9783031137143_38 9783031137143 https://library.oapen.org/handle/20.500.12657/59365 eng Graduate Texts in Operations Research application/pdf n/a 978-3-031-13714-3.pdf https://link.springer.com/978-3-031-13714-3 Springer Nature Springer International Publishing 10.1007/978-3-031-13714-3 10.1007/978-3-031-13714-3 6c6992af-b843-4f46-859c-f6e9998e40d5 07f61e34-5b96-49f0-9860-c87dd8228f26 9783031137143 Swiss National Science Foundation (SNF) Springer International Publishing 287 Cham [...] Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung Swiss National Science Foundation open access
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This 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.
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