A first course in the theory and practice of discrete-event simulation.  Monte Carlo methods, spreadsheet add-ins, and applications. Discrete-event dynamic systems, modeling, simulation logic and data structures.  Generating random numbers and variates, distribution fitting, and simulation input analysis.  Output analysis, model verification and validation, comparing alternative systems, and variance reduction.  Simulation optimization, requirements verification, and case studies.  Applications span communication, computer, distribution, financial, health-care, manufacturing, service, and transportation systems.  Coverage includes state-of-the-art software tools.