This is an advanced course on key issues in the design and analysis of computer simulation experiments on models of stochastic systems. Computer scientists, financial analysts, industrial engineers, management scientists, operations researchers (and many other professionals) use stochastic simulation to design, understand, and improve communications, financial, manufacturing, logistics, and service systems. The theme that runs throughout these diverse applications is the need to evaluate system performance in the face of uncertainty. To serve this purpose, this course surveys the concepts, principles, tools, and techniques that underlie the theory and practice of stochastic simulation design and analysis, emphasizing ideas and methods that are likely to remain an intrinsic part of the foundation of the field for the foreseeable future. Upon completion of the course you will be able to carry out the entire process of designing the model, implementing it in the appropriate software, executing the simulation, collecting and analyzing output data, and using the results of the analysis to evaluate alternative decisions.
Lecture: 100min/wk and Recitation: 50min/wk