New Optimization Techniques in Engineering - Godfrey C. Onwubolu

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Résumé :
Presently, general-purpose optimization techniques such as Simulated Annealing, and Genetic Algorithms, have become standard optimization techniques. Concerted research efforts have been made recently in order to invent novel optimization techniques for solving real life problems, which have the attributes of memory update and population-based search solutions. The book describes a variety of these novel optimization techniques which in most cases outperform the standard optimization techniques in many application areas. New Optimization Techniques in Engineering reports applications and results of the novel optimization techniques considering a multitude of practical problems in the different engineering disciplines - presenting both the background of the subject area and the techniques for solving the problems.

Sommaire:
1: Introduction.- 2: Introduction to Genetic Algorithms for Engineering Optimization.- 3: Memetic Algorithms.- 4: Scatter Search and Path Relinking: Foundations and Advanced Designs.- 5: Ant Colony Optimization.- 6: Differential Evolution.- 7: SOMA - Self-Organizing Migrating Algorithm.- 8: Discrete Particle Swarm Optimization, illustrated by the Traveling Salesman Problem.- 9: Applications in Heat Transfer.- 10: Applications in Mass Transfer.- 11: Applications in Fluid Mechanics.- 12: Applications in Reaction Engineering.- 13: New Ideas and Applications of Scatter Search and Path Relinking.- 14: Improvement of Search Process in Genetic Algorithms: An Application of PCB Assembly Sequencing Problem.- 15: An ANTS Heuristic for the Long-Term Car Pooling Problem: ACO.- 16: Genetic Algorithms in Irrigation Planning: A Case Study of Sri Ram Sagar Project, India.- 17: Optimization of Helical Antenna Electromagnetic Pattern Field.- 18: VLSI design: Gate Matrix Layout Problem.- 19: Parametric Optimization of a Fuzzy Logic Controller for Nonlinear Dynamical Systems using Evolutionary Computation.- 20: DNA Coded GA: Rule Base Optimization of FLC for Mobile Robot.- 21: TRIBES application to the flow shop scheduling problem.- 22: Optimizing CNC Drilling Machine Operations: Traveling Salesman Problem-Differential Evolution Approach.- 23: Particle swarm optimization for the assignment of facilities to locations.- 24: Differential Evolution for the Flow Shop Scheduling Problem.- 25: Evaluation of Form Errors to Large Measurement Data Sets Using Scatter Search.- 26: Mechanical engineering problem optimization by SOMA.- 27: Scheduling and Production & Control: MA.- 28: Determination of Optimal Machining Conditions Using Scatter Search.- 29: Extended Frontiers in optimization techniques.