Metaheuristics for Hard Optimization
Methods and Case Studies
-
- $109.99
-
- $109.99
Publisher Description
Metaheuristics for Hard Optimization comprises of three parts. The first part is devoted to the detailed presentation of the four most widely known metaheuristics:
• the simulated annealing method,
• tabu search,
• the evolutionary algorithms,
• ant colony algorithms.
Each one of these metaheuristics is actually a family of methods, of which the essential elements are discussed. In the second part, the book presents some other less widespread metaheuristics, then, extensions of metaheuristics and some ways of research are described . The problem of the choice of a metaheuristic is posed and solution methods are discussed. The last part concentrates on three case studies from telecommunications, air traffic control, and vehicle routing.
Adaptive Representations for Reinforcement Learning
2008
Issues in the Use of Neural Networks in Information Retrieval
2009
Differential Evolution
2007
Artificial Neural Networks in Vehicular Pollution Modelling
2009
Evolutionary Based Solutions for Green Computing
2011
Computational Intelligence in Expensive Optimization Problems
2010