Genetic Algorithms in Electromagnetics focuses onoptimizing the objective function when a computer algorithm, analytical model, or experimental result describes the performanceof an electromagnetic system. It offers expert guidance tooptimizing electromagnetic systems using genetic algorithms (GA), which have proven to be tenacious in finding optimal results wheretraditional techniques fail.
Genetic Algorithms in Electromagnetics begins with anintroduction to optimization and several commonly used numericaloptimization routines, and goes on to feature:
- Introductions to GA in both binary and continuous variableforms, complete with examples of MATLAB(r) commands
- Two step-by-step examples of optimizing antenna arrays as wellas a comprehensive overview of applications of GA to antenna arraydesign problems
- Coverage of GA as an adaptive algorithm, including adaptive andsmart arrays as well as adaptive reflectors and crosseddipoles
- Explanations of the optimization of several different wireantennas, starting with the famous "crooked monopole"
- How to optimize horn, reflector, and microstrip patch antennas, which require significantly more computing power than wireantennas
- Coverage of GA optimization of scattering, including scatteringfrom frequency selective surfaces and electromagnetic band gapmaterials
- Ideas on operator and parameter selection for a GA
- Detailed explanations of particle swarm optimization andmultiple objective optimization
- An appendix of MATLAB code for experimentation