- Semester
- Fall 2024
- Instructor
- Zimo Wang
- Start Date
- 08-21-2024
- Total Credits
- 3
- Call to Register
- 607-777-6088
Take your class online with SUNY
You will learn the same curriculum as our on-campus students
This course is a survey of the newer, most common adaptive search methods. This is a project- and research-oriented course designed to give graduate students a foundation from which to explore areas of their own interest. Focused topics include simulated annealing, genetic algorithms, evolution strategies, tabu search, ant colony methods, and particle swarm optimization. Other search methods such as genetic programming, evolutionary programming and random search methods will be briefly covered. Major emphasis is on NP complete combinatorial problems found in engineering. Issues such as solution encodings, stochastic convergence, selection methods, local and global search methods are discussed. Prerequisite: SSIE 505 or equivalent, SSIE 520, and knowledge of at least one programming language. Offered in the Fall semester. 3 credits.
Prerequisites:
Prerequisite: SSIE 505 or equivalent, SSIE 520, and knowledge of at least one programming language.
Course Area: Engineering
Level: Graduate
Dates: 08-21-2024 - 12-06-2024
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- Instructor: Zimo Wang
- Local Course ID: 24FA_BIN_SSIE644_20
- Books & Supplies
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