An introduction to the basic concepts of simulating complex systems by computer. Emphasis is on modeling and problem solving. A survey of probabilistic methods for solving decision problems under uncertainty. Probability review, queueing theory, inventory models, Markov decision processes, reliability, decision theory and games, and simulation are covered.
Emphasis is on modeling and problem solving.
An examination of optimization models as applied to business problems. Both linear and nonlinear models are considered including dynamic, integer, and goal programming. Applications to management, finance, and marketing are presented. Modern numerical methods and software. Emphasis is on problem solving through software and assessing the quality of solutions obtained.