In this lecture, we dive deeper into the basic Genetic Algorithm by describing the three major operators in any GA iteration – the selection operator, the crossover operator, and the mutation operator. We describe different forms of selection (fitness proportionate, ranking, and tournament) and how they vary in their ability to control selection pressure. We also discuss several forms of crossover (from single point to multi-point to uniform to taking random linear combinations) and their function as they move individuals around fitness landscapes. We will finish with the mutation operator next time, but that content is also covered in the pre-written slide notes linked below. After discussing the mutation operator and some optimizations of the GA itself, we will transition next to to evolutionary computing/programming.
Whiteboard notes for this lecture can be found at:
https://www.dropbox.com/scl/fi/sa96xjlv5d8q3mc8l0bde/IEE598-Lecture1F-2026-01-29-Operators_of_the_Genetic_Algorithm-Notes.pdf?rlkey=54eow2a79g1437r7g19be7gjy&dl=0
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