Evolutionary Optimization
Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques...
| Main Authors: | , , |
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| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boston, MA :
Springer US,
2002.
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| Series: | International Series in Operations Research & Management Science,
48 |
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Table of Contents:
- Conventional Optimization Techniques
- Evolutionary Computation
- Single Objective Optimization
- Evolutionary Algorithms and Constrained Optimization
- Constrained Evolutionary Optimization
- Multi-Objective Optimization
- Evolutionary Multi-Objective Optimization: A Critical Review
- Multi-Objective Evolutionary Algorithms for Engineering Shape Design
- Assessment Methodologies for Multiobjective Evolutionary Algorithms
- Hybrid Algorithms
- Utilizing Hybrid Genetic Algorithms
- Using Evolutionary Algorithms to Solve Problems by Combining Choices of Heuristics
- Constrained Genetic Algorithms and Their Applications in Nonlinear Constrained Optimization
- Parameter Selection in EAs
- Parameter Selection
- Application of EAs to Practical Problems
- Design of Production Facilities Using Evolutionary Computing
- Virtual Population and Acceleration Techniques for Evolutionary Power Flow Calculation in Power Systems
- Application of EAs to Theoretical Problems
- Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions
- A Genetic Algorithm Heuristic for Finite Horizon Partially Observed Markov Decision Problems
- Using Genetic Algorithms to Find Good K-Tree Subgraphs.
