Taking a practical approach, Design and Modeling for Computer Experiments presents the most useful design and modeling methods for computer simulations used to study physical systems. The authors introduce the basic concepts of design as well as the concept of Latin hypercube sampling and its modifications. They cover uniform design, measures of uniformity, and their algebraic equations. They also provide various stochastic optimization techniques along with a variety of popular algorithms, such as simulated annealing, stochastic evolutionary, and threshold acceptance. The text includes discussions on special techniques for model interpretation, including generalized ANOVA and the Fourier Amplitude Sensitivity Test.