Theory Of Randomized Search Heuristics Foundations And Recent Developments
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Theory of Randomized Search Heuristics
This volume covers both classical results and the most recent theoretical developments in the field of randomized search heuristics such as runtime analysis, drift analysis and convergence.
Theory Of Randomized Search Heuristics: Foundations And Recent Developments
Randomized search heuristics such as evolutionary algorithms, genetic algorithms, evolution strategies, ant colony and particle swarm optimization turn out to be highly successful for optimization in practice. The theory of randomized search heuristics, which has been growing rapidly in the last five years, also attempts to explain the success of the methods in practical applications.This book covers both classical results and the most recent theoretical developments in the field of randomized search heuristics such as runtime analysis, drift analysis and convergence. Each chapter provides an overview of a particular domain and gives insights into the proofs and proof techniques of more specialized areas. Open problems still remain widely in randomized search heuristics — being a relatively young and vast field. These problems and directions for future research are addressed and discussed in this book.The book will be an essential source of reference for experts in the domain of randomized search heuristics and also for researchers who are involved or ready to embark in this field. As an advanced textbook, graduate students will benefit from the comprehensive coverage of topics
Recent Developments in Metaheuristics
This book highlights state-of-the-art developments in metaheuristics research. It examines all aspects of metaheuristic research including new algorithmic developments, applications, new research challenges, theoretical developments, implementation issues, in-depth experimental studies. The book is divided into two sections. Part I is focused on new optimization and modeling techniques based on metaheuristics. The chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics optimization methodology, designing genetic algorithms, and also the cuckoo search algorithm. The techniques described help to enhance the usability and increase the potential of metaheuristic algorithms. Part II showcases advanced metaheuristic approaches to solve real-life applications issues. This includes an examination of scheduling, the vehicle routing problem, multimedia sensor network, supplier selection, bin packing, objects tracking, and radio frequency identification. In the fields covered in the chapters are of high-impact applications of metaheuristics. The chapters offer innovative applications of metaheuristics that have a potential of widening research frontiers. Altogether, this book offers a comprehensive look at how researchers are currently using metaheuristics in different domains of design and application.