Courses
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Descriptions
IEMS 450-1: Mathematical Optimization I

Quarter Offered

Fall : MW 9:30-10:50 ; Küçükyavuz

Prerequisites

Linear algebra and calculus

Description

Linear programming formulation, simplex algorithm, optimality conditions, duality, practical computation, extensions, applications, and case studies.

Learning Objectives

Students will learn the foundations of linear programming, properties of optimal solutions and various solution methods for optimizing problems involving a linear objective function and linear constraints. Students will be exposed to geometric, algebraic and computational aspects of linear optimization and its extensions.

Topics 

  • Geometry of Linear Programming (LP)
  • Polyhedra, extreme points, degeneracy
  • Simplex method
  • Duality
  • Complexity of LP, ellipsoid method
  • Large-scale optimization
  • Network flows
  • Integer linear programming

Materials

Introduction to Linear Optimization, by D. Bertsimas and J. N. Tsitsiklis, Athena Scientific, 1997

Prerequisites

Linear algebra and calculus