Core Courses:

STOR 641 Stochastic Models in Operations Research I (Prerequisite, STOR 435 or equivalent.) Review of probability, conditional probability, expectations, transforms, generating functions, special distributions, functions of random variables. Introduction to stochastic processes. Discrete-time Markov chains. Transient and limiting behavior. First passage times. (Fall; Ziya)

STOR 642 Stochastic Models in Operations Research II (Prerequisite, STOR 641 or equivalent.) Exponential distribution and Poisson process. Birth-death processes, continuous-time Markov chains. Transient and limiting behavior. Applications to elementary queueing theory. Renewal processes and regenerative processes. (Spring; Kulkarni)

STOR 672 Simulation Modeling and Analysis (Prerequisites: STOR 555 and 641.) Familiarity with computer programming required. Introduces students to modeling, programming, and statistical concepts applicable to discrete event simulation on digital computers. Emphasizes statistical analysis of simulation output. Students model, program, and run simulations. (Spring; Argon)

STOR 743 Stochastic Models in Operations Research III (Prerequisite, STOR 642 or equivalent.) Intermediate queueing theory, queueing networks. Reliability. Diffusion processes and applications. Markov decision processes (stochastic dynamic programming): finite horizon, infinite horizon, discounted and average-cost criteria. (Fall; Argon, Ziya)

Special Topics Courses:

• STOR 892. Data driven decision models (Fall 2018; Kulkarni)
• STOR 893. Analytics: Exploration of the Academic Literature (Spring 2017; Ziya)
• STOR 892. Stochastic Models in Health Care (Fall 2016; Kulkarni)
• STOR 892. Advanced Topics and Applications in Markov Decision Processes (Spring 2016; Ziya)
• STOR 890. Design and Control of Queueing Systems with Applications to Manufacturing and Health Care (Spring 2020; Argon)
• STOR 891. Market Dynamics (Fall 2014; Kulkarni)
• STOR 891. Modeling and Analysis of Service Operations (Spring 2014; Ziya)