Optimization And Simulation Models

Catalog description

Problem Formulation and solution for a variety of complex engineering problems, using Optimization methods, including linear programming, nonlinear programming, dynamic programming and artificial intelligence based optimization. Use of analytical techniques and computer software to solve formulated real world problems using simulation models. Typically offered Fall Spring Summer. Course Learning Outcomes 1. Apply a process and design the problem formulation and constraints for real world processes. 2. Discover the limitations of the mathematical modeling process and examine and understand the results. 3. Introduce artificial intelligence and hybrid models and their applications in engineering. View Class Schedule