Occasionally offered during the fall semester.

Catalog description:

Presentation of theory, computational techniques, and general applications of linear, integer, and parametric programming; decomposition and network flow principles.

Prerequisites: MTH 222 or 231 and CSA273 or equivalent.

Objectives:

• To build problem formulation and modeling skills.
• To study optimization techniques based on linear and nonlinear programming algorithms.
• To learn about the real-life applications of these techniques.

Required topics (approximate weeks allocated):

• Review of linear programming (2)
  • LP formulations
  • graphical solution
  • the simplex method
• Compact forms of LP models (3)
  • the simplex method in matrix notation
  • sensitivity analysis of LP solutions
  • duality
• Integer programming (3)
  • problem formulation with integer variables
  • the branch & bound solution method
  • implicit enumeration method
  • computational complexity issues
• Nonlinear programming (3)
  • solving one-variable NLP
  • unconstrained NLPs
  • constrained NLPs
  • Lagrange multipliers
• Dynamic programming (3)
  • DP formulation of sequential decision processes
  • backward recursive solution
  • forward recursive solution
• Exams/Review (1)