Overview

Course Objectives:

Development of modeling skills

  • Modeling and analyzing systems with optimization models
  • Practice in the application of OR/MS techniques:
    • Linear, integer, nonlinear, multi-objective, stochastic programming
    • Specific classes of models that use these formulations: networks, data analysis, financial, telecommunications,  logistics

Acquaint the student with modern modeling software

  • Hands-on use of commercial optimizers and modeling support tools: GAMS, OPL
  • Understand the principles of decision support system (DSS) design
    • DSS components
    • Usability issues
    • Model management

Teaching Approach: Case Studies and Lectures

  • Introductory lectures on each topic
  • Case studies of industrial and governmental  applications
    • Cases are prepared prior to class
    • Class discussions of each case are led by students, and alternate approaches to the same problem situation are compared
  • Because of the highly interactive nature of the  course, it is not available via distance education

Texts:

  • Barr, Optimization Models for  Decision Support, Class Notes (available from Alphagraphics)

Hint: don’t understand a term, like hurdle rate? Try google.com with “define:hurdle rate” as the query. Or dictionary.com.

Term Project
Develop a case study for a (preferably real) problem, formulate a model for it, and, if possible, solve the model with a modeling language. To be turned in: a report with the case study and your solution for it, in both hard and soft copy forms. Each class member will present their project to the class at the final exam time.