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At the Illinois Genetic Algorithms Laboratory (IlliGAL), we study nature’s search algorithm of choice, genetics and evolution, as a practical approach to solving difficult problems on a computer. Genetic algorithms (GAs) and evolutionary computation have been around since the the cybernetics movement of 1950s, but they have undergone a renaissance since the mid-1980s to the point where many walks of human endeavor are benefiting from this approach. For example, problems as different as jet engine design, electromagnetic antenna-absorber optimization and design, analog and logic electronic circuit synthesis, structural optimization and layout, factory and project scheduling, control system synthesis, music composition, image recognition, and automated programming have been successfully tackled. Theory and empirical results demonstrate well-designed GAs can be guaranteed to solve a broad class of provably hard problems, quickly, reliably, and accurately.