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Autorenporträt
Inhaltsangabe
Introduction.- Incomplete Solution Representations and Decoders.- Hybridization Based on Problem Instance Reduction.- Hybridization Based on Large Neighborhood Search.- Making Use of a Parallel, Non-independent, Construction of Solutions Within Metaheuristics.- Hybridization Based on Complete Solution Archives.- Further Hybrids and Conclusions.
Introduction.- Incomplete Solution Representations and Decoders.- Hybridization Based on Problem Instance Reduction.- Hybridization Based on Large Neighborhood Search.- Making Use of a Parallel, Non-independent, Construction of Solutions Within Metaheuristics.- Hybridization Based on Complete Solution Archives.- Further Hybrids and Conclusions.
Rezensionen
"From the perspective of a practitioner with real-world experience in combinatorial optimization, the text is comprehensive, and at the same time it offers fresh angles and shares valuable expertise. ... I highly recommend this book, both to practitioners and theoreticians at the post graduate levels, be they rooted either at the 'formal/rigid' or 'heuristic/soft' ends of Combinatorial Optimization research or practice." (Ofer M. Shir, Genetic Programming and Evolvable Machines, Vol. 19 (1-2), June, 2018)
"This book by Blum and Raidl constructs a bridge between these two approaches and aims to share expertise gained from each end. ... The book is well-structured. ... I highly recommend this book,both to practitioners and theoreticians at the post graduate levels, be they rooted either at the 'formal/rigid' or 'heuristic/soft' ends of Combinatorial Optimization research or practice." (Ofer M. Shir, Genetic Programming and Evolvable Machines, Vol. 19 (1-2), June, 2018)
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