An introduction to optimization through mathematical programming and stochastic modeling techniques. Course topics include linear programming, and transportation and assignment algorithms. Special attention is placed on sensitivity analysis and the need of optimization in decision-making. The course is delivered through lectures and a weekly laboratory where students learn to use state-of-the-art software packages for modeling large discrete optimization problems.

A basic course in quantitative models on layout, material handling, and warehousing. Topics include product/process analysis, flow of materials, material handling systems, warehousing and layout design. A computer-aided layout design package is used.

Time value of money, methods of comparing alternatives, depreciation and depletion, income tax consideration and capital budgeting. Cannot be used as a professional elective for ISE majors. Course provides a foundation for engineers to effectively analyze engineering projects with respect to financial considerations.

A first course in mathematical modeling of production-inventory systems. Topics included: Inventory: Deterministic Models, Inventory: Stochastic Models, Push v. Pull Production Control Systems, Factory Physics, and Operations Scheduling. Modern aspects such as lean manufacturing are included in the context of the course.

One semester of paid work experience in industrial engineering.

Simulation and queueing theory are used to design and evaluate the performance of dynamic and stochastic systems. Queueing methods are utilized to study waiting line systems. Digital simulation is applied to the design and analysis of complex systems in a variety of contexts using powerful simulation tools. The course will emphasize simulation modeling and statistical analysis techniques essential for conducting simulation projects.

This course discusses several strategic, tactical, and operational concepts used in improving the distribution of goods and services by companies worldwide. The course emphasis is on understanding when and how these concepts are applied, as well as on using mathematical programming and optimization methods for their adequate implementation.

In conference with a faculty adviser, an independent engineering project or research problem is selected. The work may be of a theoretical and/or computational nature. A state-of-the-art literature search in the area is normally expected. A formal written thesis and an oral defense with a faculty thesis committee are required. Submission of bound copies of the thesis to the library and to the department and preparation of a written paper in a short format suitable for submission for publication in a refereed journal are also required. Approval of department head and faculty adviser needed to enroll.

This class introduces students to state of the art research and research methods in industrial and systems engineering. Presentations include off campus speakers and students/faculty presentations on current research under way in the department.