Design of Modern Heuristics :
Rothlauf, Franz.
Design of Modern Heuristics : Principles and Application / by Franz Rothlauf. - xI, 267 páginas recurso en línea. - Natural Computing Series, 1619-7127 .
Springer eBooks
Chap. 1 -- Introduction -- Part I -- Fundamentals -- Chap. 2 -- Optimization Problems -- Chap. 3 -- Optimization Methods -- Part II -- Modern Heuristics -- Chap. 4 -- Design Elements -- Chap. 5 -- Search Strategies -- Chap. 6 -- Design Principles -- Part III Case Studies -- Chap. 7 -- High Locality Representations for Automated Programming -- Chap. 8.-Biased Modern Heuristics for the OCST Problem -- Chap. 9.-Summary -- References -- Nomenclature -- Glossary -- Index.
Most textbooks on modern heuristics provide the reader with detailed descriptions of the functionality of single examples like genetic algorithms, genetic programming, tabu search, simulated annealing, and others, but fail to teach the underlying concepts behind these different approaches. The author takes a different approach in this textbook by focusing on the users' needs and answering three fundamental questions: First, he tells us which problems modern heuristics are expected to perform well on, and which should be left to traditional optimization methods. Second, he teaches us to systematically design the "right" modern heuristic for a particular problem by providing a coherent view on design elements and working principles. Third, he shows how we can make use of problem-specific knowledge for the design of efficient and effective modern heuristics that solve not only small toy problems but also perform well on large real-world problems. This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
9783540729624
10.1007/9783540729624 doi
Q334-342
Design of Modern Heuristics : Principles and Application / by Franz Rothlauf. - xI, 267 páginas recurso en línea. - Natural Computing Series, 1619-7127 .
Springer eBooks
Chap. 1 -- Introduction -- Part I -- Fundamentals -- Chap. 2 -- Optimization Problems -- Chap. 3 -- Optimization Methods -- Part II -- Modern Heuristics -- Chap. 4 -- Design Elements -- Chap. 5 -- Search Strategies -- Chap. 6 -- Design Principles -- Part III Case Studies -- Chap. 7 -- High Locality Representations for Automated Programming -- Chap. 8.-Biased Modern Heuristics for the OCST Problem -- Chap. 9.-Summary -- References -- Nomenclature -- Glossary -- Index.
Most textbooks on modern heuristics provide the reader with detailed descriptions of the functionality of single examples like genetic algorithms, genetic programming, tabu search, simulated annealing, and others, but fail to teach the underlying concepts behind these different approaches. The author takes a different approach in this textbook by focusing on the users' needs and answering three fundamental questions: First, he tells us which problems modern heuristics are expected to perform well on, and which should be left to traditional optimization methods. Second, he teaches us to systematically design the "right" modern heuristic for a particular problem by providing a coherent view on design elements and working principles. Third, he shows how we can make use of problem-specific knowledge for the design of efficient and effective modern heuristics that solve not only small toy problems but also perform well on large real-world problems. This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
9783540729624
10.1007/9783540729624 doi
Q334-342