Dec 06, 2021
CS 471 - Optimization
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: CS 302 and CS 325 and MATH 330 with a grade of C or higher in each course.
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:
Anticipated Course Offering Terms and Locations:
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