<p><P>Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and
Hybrid Metaheuristics: An Emerging Approach to Optimization
β Scribed by Christian Blum, Maria Jose Blesa Aguilera, Andrea Roli, Michael Sampels
- Publisher
- Springer
- Year
- 2008
- Tongue
- English
- Leaves
- 293
- Series
- Studies in Computational Intelligence
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Optimization problems are of great importance across a broad range of fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments. The authors involved in this book are among the top researchers in their domain.
π SIMILAR VOLUMES
Heuristic methods are used when rigorous ones are either unknown or cannot be applied, typically because they would be too slow. A metaheuristic is a general optimization framework that is used to control an underlying problem-specific heuristic such that the method can be easily applied to diffe
<p><span>This book provides a comprehensive study of structural design and optimization of different truss structures for size, shape, and topology of structure. It describes truss optimization based on into three categories: size optimization, shape optimization, and topology optimization.</span></
<p><OL><LI>Metaheuristics: Intelligent Problem Solving</LI><P><EM>Marco Caserta and Stefan VoΓ</EM></P><P></P><P><LI>Just MIP it!</LI><P></P><P><EM>Matteo Fischetti, Andrea Lodi, and Domenico Salvagnin</EM></P><P></P><P><LI>MetaBoosting: Enhancing Integer Programming Techniques by Metaheuristics</LI
<p><OL><LI>Metaheuristics: Intelligent Problem Solving</LI><P><EM>Marco Caserta and Stefan VoΓ</EM></P><P></P><P><LI>Just MIP it!</LI><P></P><P><EM>Matteo Fischetti, Andrea Lodi, and Domenico Salvagnin</EM></P><P></P><P><LI>MetaBoosting: Enhancing Integer Programming Techniques by Metaheuristics</LI
This book describes a general hybrid metaheuristic for combinatorial optimization labeled Construct, Merge, Solve & Adapt (CMSA). The general idea of standard CMSA is the following one. At each iteration, a number of valid solutions to the tackled problem instance are generated in a probabilistic wa