Reactive Search and Intelligent Optimization
Reactive Search integrates sub-symbolic machine learning techniques into search heuristics for solving complex optimization problems. By automatically adjusting the working parameters, a reactive search self-tunes and adapts, effectively learning by doing until a solution is found. Intelligent Optim...
| Main Authors: | Battiti, Roberto (Author), Brunato, Mauro (Author), Mascia, Franco (Author) |
|---|---|
| Corporate Author: | SpringerLink (Online service) |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boston, MA :
Springer US,
2009.
|
| Series: | Operations Research/Computer Science Interfaces Series,
45 |
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Similar Items
-
Search Methodologies Introductory Tutorials in Optimization and Decision Support Techniques /
Published: (2005) -
Optimization by GRASP Greedy Randomized Adaptive Search Procedures /
by: Resende, Mauricio G.C, et al.
Published: (2016) -
Metaheuristic Optimization via Memory and Evolution Tabu Search and Scatter Search /
Published: (2005) -
Handbook of Metaheuristics
Published: (2010) -
Linear Programming Foundations and Extensions /
by: Vanderbei, Robert J.
Published: (2008)