Applied Optimization

Catalog description

This course provides an introduction to systems optimization focusing on understanding system tradeoffs. The course introduces modeling methodology (linear, integer, stochastic, dynamic, and nonlinear programming), with applications in production planning, scheduling and manpower planning, time-phased planning, inventory and logistics management, supply chain network design, facility sizing and capacity expansion, capital budgeting models, assignment and matching, and transportation models. In this class, students learn powerful modeling and solution techniques for decision-making problems that are used today by thousands of successful companies to help them to reduce their operation costs and therefore saving millions of dollars. The course covers some of the optimization methods such as simplex method, duality analysis, branch-and-bound, and KKT Conditions for solving nonlinear convex programming problems.