Major dimensions of systems engineering will be covered and demonstrated through case studies: (1) The history, philosophy, art, and science upon which systems engineering is grounded; including system thinking and guiding principles and steps in the `systems engineering approach¿ to problem solving; and (2) The basic tools of systems engineering analysis, including; goal definition and system representation, requirements analysis, system assessment and evaluation, mathematical modeling, and decision analysis.

Detailed study of a selected topic determined by the current interest of faculty and students. Offered as required. Prerequisite: As specified for each offering.

Detailed study of a selected topic, determined by the current interest of faculty and students. Offered as required.

Introduction to deterministic optimization models: theory, algorithms, and applications. Coverage begins with highly structured network optimization models and ends with unstructured linear optimization models. Applications include (1) telecommunications network planning and design, (2) design and utilization of transportation and distribution networks, and (3) project management and scheduling. Corequisite: SYS 2001 and APMA 3080.

A third-year level undergraduate course focused on a topic not normally covered in the course offerings. The topic usually reflects new developments in the systems and information engineering field. Offering is based on student and faculty interests. Prerequisites: Instructor Permission

A design project extending throughout the fall and spring semesters. Involves the study of a real-world, open-ended situation, including problem formulation, data collection, analysis and interpretation, model building and analysis, and generation of solutions. Students work on the same project with the same team in SYS 4053 and 4054 in subsequent semesters.  Pre-requisites: SYS 2001 and SYS 2202 and FOUR of the following (SYS 3021 or SYS 3023 or SYS 3034 or SYS 3060 or  SYS 3062)

Independent study or project research under the guidance of a faculty member. Offered as required. Prerequisite: As specified for each offering.

This course is an introduction to theory and application of mathematical optimization. The goal of this course is to endow the student with a) a solid understanding of the subject's theoretical foundation and b) the ability to apply mathematical programming techniques in the context of diverse engineering problems. Topics to be covered include a review of convex analysis (separation and support of sets, application to linear programming), convex programming (characterization of optimality, generalizations), Karush-Kuhn-Tucker conditions, constraint qualification and Lagrangian duality. The course closes with a brief introduction to dynamic optimization in discrete time. Prerequisite: Two years of college mathematics, including linear algebra, and the ability to write computer programs.

Introduces modeling, analysis, and control of dynamic systems, using ordinary differential and difference equations. Emphasizes the properties of mathematical representations of systems, the methods used to analyze mathematical models, and the translation of concrete situations into appropriate mathematical forms. Primary coverage includes ordinary linear differential and difference equation models, transform methods and concepts from classical control theory, state-variable methods and concepts from modern control theory, and continuous system simulation. Applications are drawn from social, economic, managerial, and physical systems. Cross-listed as MAE 6620. Prerequisite: APMA 2130 or equivalent.

This course shows how to use linear statistical models for analysis in engineering and science. The course emphasizes the use of regression models for description, prediction, and control in a variety of applications. Building on multiple regression, the course also covers principal component analysis, analysis of variance and covariance, logistic regression, time series methods, and clustering. Course lectures concentrate on theory and practice.