Adaptive and Multilevel Metaheuristics
Springer Berlin (Verlag)
978-3-642-09833-8 (ISBN)
One of the keystones in practical metaheuristic problem-solving is the fact that tuning the optimization technique to the problem under consideration is crucial for achieving top performance. This tuning/customization is usually in the hands of the algorithm designer, and despite some methodological attempts, it largely remains a scientific art. Transferring a part of this customization effort to the algorithm itself -endowing it with smart mechanisms to self-adapt to the problem- has been a long pursued goal in the field of metaheuristics.
These mechanisms can involve different aspects of the algorithm, such as for example, self-adjusting the parameters, self-adapting the functioning of internal components, evolving search strategies, etc.
Recently, the idea of hyperheuristics, i.e., using a metaheuristic layer for adapting the search by selectively using different low-level heuristics, has also been gaining popularity. This volume presents recent advances in the area of adaptativeness in metaheuristic optimization, including up-to-date reviews of hyperheuristics and self-adaptation in evolutionary algorithms, as well as cutting edge works on adaptive, self-adaptive and multilevel metaheuristics, with application to both combinatorial and continuous optimization.
Reviews of the Field.- Hyperheuristics: Recent Developments.- Self-Adaptation in Evolutionary Algorithms for Combinatorial Optimisation.- New Techniques and Applications.- An Efficient Hyperheuristic for Strip-Packing Problems.- Probability-Driven Simulated Annealing for Optimizing Digital FIR Filters.- RASH: A Self-adaptive Random Search Method.- Market Based Allocation of Transportation Orders to Vehicles in Adaptive Multi-objective Vehicle Routing.- A Simple Evolutionary Algorithm with Self-adaptation for Multi-objective Nurse Scheduling.- Individual Evolution as an Adaptive Strategy for Photogrammetric Network Design.- Adaptive Estimation of Distribution Algorithms.- Initialization and Displacement of the Particles in TRIBES, a Parameter-Free Particle Swarm Optimization Algorithm.- Evolution of Descent Directions.- "Multiple Neighbourhood" Search in Commercial VRP Packages: Evolving Towards Self-Adaptive Methods.- Automated Parameterisation of a Metaheuristic for the Orienteering Problem.
| Erscheint lt. Verlag | 28.10.2010 |
|---|---|
| Reihe/Serie | Studies in Computational Intelligence |
| Zusatzinfo | XV, 275 p. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 442 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Technik | |
| Schlagworte | Adaptive Metaheuristics • algorithm • algorithms • Evolution • evolutionary algorithm • Function • Heuristics • Layer • Metaheuristic • Metaheuristics • Multilevel Metaheuristics • Optimization • particle swarm • Particle swarm optimization • Probability • Problem-Solving • search strategy • Virtual Reality |
| ISBN-10 | 3-642-09833-9 / 3642098339 |
| ISBN-13 | 978-3-642-09833-8 / 9783642098338 |
| Zustand | Neuware |
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