CS 471 - Optimization

Description:
Unimodal and Multimodal problems; combinatorial optimization problems; deterministic algorithms; Hill climbing algorithm; Tabu Search Algorithm; Evolutionary algorithms; Particle swarm optimization; Differential evolution; Single and Mutli-objective optimization.

Prerequisites:
Prerequisites: CS 302 and CS 325 and MATH 330 with a grade of C or higher in each course.

Credits: (4)

Learner Outcomes:
Upon successful completion of this course, the student will be able to:

Demonstrate knowledge of different problem domains.
Differentiate different optimization algorithm classification, in terms of deterministic and stochastic algorithms.
Formulate deterministic algorithms using given set of rules on a specified problem domain.
Formulate stochastic algorithms based on population topology.
Assess the performance characteristics of different algorithms through benchmark tests.
Evaluate the suitability of different optimization algorithms in given scenarios.

Learner Outcomes Approval Date:
3/6/20

Anticipated Course Offering Terms and Locations: