Apple Academic Press
652 pages | 34 Color Illus. | 172 B/W Illus.
Edited by professionals with years of experience, this bookprovides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applications. Covering both the theory and applications of evolutionary computation, the book offers exhaustive coverage of several topics on nontraditional evolutionary techniques, details working principles of new and popular evolutionary algorithms, and discusses case studies on both scientific and real-world applications of optimization
Theory and Applications in Engineering Systems. Introduction. Bio-Mimetic Adaptations of Genetic Algorithm and Their Applications to Chemical Engineering. Surrogate-Assisted Evolutionary Computing Methods. Evolutionary Algorithms in Ironmaking Applications. Harmony Search Optimization for Multilevel Thresholding in Digital Images. Swarm Intelligence in Software Engineering Design Problems. Gene Expression Programming in Nanotechnology Applications. Theory and Applications of Single Objective Optimization Studies. An Alternate Hybrid Evolutionary Method for Solving MINLP Problems. Differential Evolution for Optimal Design of Shell-and-Tube Heat Exchangers. Evolutionary Computation Based QoS-Aware Multicast Routing. Performance Assessment of the Canonical Genetic. An Efficient Approach for Populating Deep Web Repositories Using SFLA. Closed Loop Simulation of Quadraple Tank Process Using Adaptive Multi-Loop Fractional. Theory and Applications of Single and Multi-Objective Optimization Studies. A Practical Approach towards Multi Objective Shape Optimization. Nature-Inspired Computing Techniques for Integer Factorization. Genetic Algorithm Based Real-Time Parameter Identifier for an Adaptive Power System Stabilizer. Applied Evolutionary Computation in Fire Safety Upgrading. Elitist Multi-Objective Evolutionary Algorithms for Voltage and Reactive Power Optimization in Power Systems. Evaluation of Simulated Annealing, Differential Evolution and Particle Swarm Optimization for Solving Pooling Problems. Performance Improvement of NSGA-II Algorithm by Modifying Crossover Probability Distribution. Evolutionary Algorithms for Malware Detection and Classification. Index.