Multi-Objective Optimization Evolutionary to Hybrid Framework /
This book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving variou...
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| Other Authors: | , , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Singapore :
Springer Singapore : Imprint: Springer,
2018.
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| Edition: | 1st ed. 2018. |
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Table of Contents:
- Chapter 1. An Advance Overview of Single and Multi-Objective Optimization
- Chapter 2. Non-dominated Sorting Based Multi/Many Objective Optimization: Two Decades of Research and Application
- Chapter 3. Uncertain Multi-objective Portfolio Selection Model based on Genetic Algorithm
- Chapter 4. A Multiobjective Genetic Algorithm-based Approach for Identifying Relevant and Non-redundant Cancer-MicroRNA Markers
- Chapter 5. Application of Multi-objective Optimizations in Protein Structure Prediction
- Chapter 6. Multi-target Multiobjective Programming and Patrol Manpower Planning for Traffic Management via Genetic Algorithm
- Chapter 7. Multi-objective Optimization for Key Player Identification in Networks
- Chapter 8. Joint Maximization in Energy and Spectral Efficiency in Cooperative Cognitive Radio Networks
- Chapter 9. A Neoteric Multi-Objective Framework for Engineering Process Optimization: Metaheuristics and Experimental Designs based Approach
- Chapter 10. Multi/Many Objective Optimization - Hybrid Intelligent Framework
- Chapter 11. Efficiency Maximization of Multimedia Data Mining using Multiobjective Neuro-ACO Approach
- Chapter 12. Optimized Determination of Separating Hyper-Plane of an SVM - Hybrid Multiobjective Model
- Chapter 13. Efficient Cluster Head Selection in Wireless Sensor Network using Multiobjective Model
- Chapter 14. Achieving Optimized Bio-Metric Security in E-Governance by Multiobjective Neuro Approach
- Chapter 15. Advantage of Quantum Inspired Multiobjective Genetic Algorithm over Classical Multiobjective Genetic Algorithm
- Chapter 16. Optimizing Performance Parameter of Image Segmentation using Hybrid Multiobjective Framework.