Adaptation and Hybridization in Computational Intelligence
This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation t...
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| Other Authors: | , |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Edition: | 1st ed. 2015. |
| Series: | Adaptation, Learning, and Optimization,
18 |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-319-14400-9 |
Table of Contents:
- Adaptation and Hybridization in Nature-Inspired Algorithms
- Adaptation in the Differential Evolution
- On the Mutation Operators in Evolution Strategies
- Adaptation in Cooperative Coevolutionary Optimization
- Study of Lagrangian and Evolutionary Parameters in Krill Herd Algorithm
- Solutions of Non-Smooth Economic Dispatch Problems by Swarm Intelligence
- Hybrid Artifcial Neural Network for Fire Analysis of Steel Frames
- A Differential Evolution Algorithm with A Variable Neighborhood Search for Constrained Function Optimization
- A Memetic Differential Evolution Algorithm for the Vehicle Routing Problem with Stochastic Demands.