Engineering Management Master's Program (without Thesis) (M.S., 1 - 1.5 Years)

Axiomatic approach to probability; conditional probability; random variable. Commonly used discrete and continuous distributions. Expectation of a random variable; jointly distributed random variables; marginal and conditional distributions; independent random variables. Multinomial and multivariate normal distributions. Functions of random variables, moments, conditional expectation, m.g.f. and p.g.f., Markov inequality, law of large numbers, central limit theorem. Discrete-time Markov chains, Kolmogorov-Chapman equations, classification of states, steady-state probabilities. Applications from different areas.

Analysis of some specific problem areas within the context of planning and scheduling of production activities. Definition, formulation and available solution procedures for aggregate planning, lot sizing, material requirements planning, cutting stock, line balancing, single processor scheduling, multi processor scheduling problems.

In this course, the student is expected to work on a well-defined short project, covering a specific area of his/her choice. Alternatively, the work could cover any specific industrial problem and its solution or could even be a literature survey of a research topic. The end result will be a compilation of a final technical report of the study and presentation before the jury.