SYS 520: System Optimization

This course covers both the principles and practices of system optimization. The course includes both traditional mathematical treatments of optimization (including linear programming, non-linear programming, integer programming, stochastic methods such as Monte-Carlo methods, multi-objective system optimization, data envelope analysis) and practical, hands-on application with many real-world examples and student projects/exercises. Qualitative as well as quantitative approaches will be discussed. The course begins with an introduction and definitions of system, optimization, and system optimization. It then proceeds to explain the traditional mathematical tools and models used in system optimization including location, allocation, scheduling, and blending models as well as sensitivity analysis and network models. Optimized design is covered next. The course will conclude with several multi-objective optimization problems. Student projects and real-world examples will be heavily emphasized. A technical undergraduate degree (B.A. or B.S. or equivalent) is a prerequisite for this course.