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, AMPL, MODEL, CPLEX, others
• Understand the principles of decision support system (DSS) design
• DSS components
• Usability issues
• Model managemen

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 1/22 from Alphagraphics)
• Sarker & Newton, Optimization Modelling: A Practical Approach, CRC Press, 2008