MSC 521. Introduction to Operations Research. 3 Hours
This course covers methods, principles and fundamentals of deterministic and stochastic operations research. Emphasis is on the formulation and solution of mathematical models in decision making environments, the search for optimal solutions to these decisions, and the explicit treatment of uncertainty through the use of probabilistic modeling and statistical analysis. Models include linear and non linear programs, inventory and production models, decision analysis, forecasting. and queuing. Required background: probability theory.
MSC 523. Nonlinear Optimization. 3 Hours
This course concentrates on methods and engineering/management science applications of nonlinear optimization. Both single- and multi-variable methods as well as unconstrained and constrained problems are addressed. The course blends theoretical results such as the Kuhn-Tucker conditions and numerical search techniques such as conjugate directions with applications.
MSC 535. Applied Operations Research/Management Science. 3 Hours
This is a capstone course focused on the art rather than the 'science' of problem solving in management science and operations research. Emphasis is placed on the techniques of problem solving and model building, examination of unique problem cases, and a course project requiring modeling, data collection, and analysis.
Prerequisite(s): Completion of the management science core courses or equivalent.
MSC 544. Forecasting & Time Series Analysis. 3 Hours
Concentration on statistical techniques for modeling and predicting discrete time-series phenomena, with emphasis on understanding and applying forecasting tools in analysis and management settings. Both classical smoothing methods and the Box-Jenkins methodology for model identification, estimation, and prediction are presented.
Prerequisite(s): MSC 500 or equivalent.
MSC 550. Requirements Engineering and Analysis. 3 Hours
This course will provide an understanding of the essential concepts, practices, and applications of Requirements Engineering and Analysis that can be used to elicit and model requirements for systems. The students will be able to apply Requirements Engineering and Analysis techniques and deliverables to elicit requirements for different types of systems, including: product, service, enterprise and system-of-systems.
MSC 551. Systems Architecture and Model-Based Systems Engineering. 3 Hours
This course will provide an understanding of the essential concepts, practices, and applications of System Architecture, and how Systems Engineering models can be used to design and deploy a system. The students will be able to apply systems architecture and Model-Based Systems Engineering (MBSE) to model the different types of systems, including: product, service, enterprise and system-of-systems.
Prerequisites: ENM 505.
MSC 555. System Dynamics I. 3 Hours
Introduction to the methodology for modeling the dynamics of complex engineering, business, and socioeconomic systems. These models are used to study the effect of organizational policies and design in higher-order, multiple-loop, nonlinear feedback systems.
MSC 571. Data Analytics for Systems Engineers. 3 Hours
Data analytics help to enhance productivity through the application of quantitative and qualitative techniques to extract and categorize data to identify and analyze data patterns. Data analytics demand an integrated set of skills such as statistics, machine learning, and mathematics. This course will introduce students to some of the tools and basic principles of data analytics. Among the techniques, tools, and concepts that students will be introduced to are data collection, analysis of exploratory data, descriptive modeling, predictive modeling, evaluation, and effective communication of analytical outcomes.
Prerequisites: ENM 500.
MSC 572. System Simulation. 3 Hours
This course is an introduction to stochastic discrete event simulation of complex systems and human performance. Topics covered include model creation, 2D and 3D animation, the process of generating random numbers and random variables, the analysis of input data, the computer modeling of real systems, validation and variation, and the analysis of simulation output. Emphasis is on modeling real-world systems using modern software.
Prerequisite(s): ENM 500 or equivalent.
MSC 595. Current Problems. 1-3 Hours
Topics of current interest in specialized areas of Management Science.
MSC 599. Thesis. 1-6 Hours
Thesis in Management Science.