Издательство InTech, 2012. - 328 p.Genetic Algorithms (GAs) are global optimization techniques used in many real-life applications. They are one of several techniques in the family of Evolutionary Algorithms – algorithms that search for solutions to optimization problems by evolving better and better solutions.
A Genetic Algorithm starts with a population of possible solutions for the desired application. The best ones are selected to become parents and then, using genetic operators like crossover and mutation, offspring are generated. The new solutions are evaluated and added to the population and low-quality solutions are deleted from the population to make room for new solutions. The members of the population tend to get better with the increasing number of generations. When the algorithm is halted, the best member of the existing population is taken as the solution to the problem.
Genetic Algorithms have been applied in science, engineering, business and social sciences. A number of scientists have already solved many real-life problems using Genetic Algorithms. This book consists of 16 chapters organized in five sections.GAs in Automatic Control
Selection of Optimal Measuring Points Using Genetic Algorithm in the Process to Calibrate Robot Kinematic Parameters
Model Predictive Controller Employing Genetic Algorithm Optimization of Thermal Processes with Non-Convex Constraints
Enhancing Control Systems Response Using Genetic PID Controllers
Finite-Thrust Trajectory Optimization Using a Combination of Gauss Pseudospectral Method and Genetic Algorithm
Genetic Algorithm Application in Swing Phase Optimization of AK Prosthesis with Passive Dynamics and Biomechanics Considerations
GAs in Scheduling Problems
Genetic Algorithms Application to Electric Power Systems
Genetic Algorithms Implement in Railway Management Information System
GAs in Electrical and Electronics Engineering
Efficient VLSI Architecture for Memetic Vector Quantizer Design
Multiple Access System Designs via Genetic Algorithm in Wireless Sensor Networks
Genetic Algorithms in Direction Finding
Applications of Genetic Algorithm in Power System Control Centers
GAs in Pattern Recognition
Applying Genetic Algorithm in Multi Language’s Characters Recognition
Multi-Stage Based Feature Extraction Methods for Uyghur Handwriting Based Writer Identification
Towards the Early Diagnosis of Alzheimer’s Disease Through the Application of a Multicriteria Classification Model
GAs in Trading Systems
Portfolio Management Using Artificial Trading Systems Based on Technical Analysis
Genetic Algorithm Application for Trading in Market towar
