Description
Material
External Info
Description

This course offers a balance of theory and practice in numerical methods and optimization. Topics include numerical representations, error analysis, iteration, linear algebraic tools such a singular value and PLU decompositions, interpolation, curve-fitting, approximation, least squares, single and multivariable optimization, constraint optimization, integration, differentiation, and solving ordinary differential equations. Extensive computer programming using MATLAB. This course builds on and supplements knowledge from other courses, including APSC 172, APSC 174, and MTHE 235. Exclusion:MTHE 272, CIVL 222 and CMPE 271

Course Learning Outcomes (CLOs)
  • Understand the implications of floating point representation in the context of numerical methods.
  • Determine which numerical method is appropriate for a particular application, for example, fitting measured data to a curve, solving a system of linear equations, numerically integrating an ODE or optimization
  • Implement numerical methods on a computer using MATLAB, while promoting efficiency and accuracy.
  • Construct efficient and modular code for numerical methods and optimization.
  • Given a design problem description, extract the objective function with appropriate constraints for optimization.
  • Utilize both single and multi-variable optimization techniques in an engineering application.
Credit Breakdown

Lecture: 3
Lab: 0.5
Tutorial: 0

Academic Unit Breakdown

Mathematics 21
Natural Sciences 0
Complementary Studies 0
Engineering Science 21
Engineering Design 0

PREREQUISITE(S): APSC 142APSC 174MTHE 235
EXCLUSION(S): MTHE 272CIVL 222CMPE 271