In this lecture, we wrap up our discussion of Pareto ranking for Multi-Objective Evolutionary Algorithms (MOEA's) and then introduce the topic of diversity-preservation methods ("niching" methods) that maintain diversity across the Pareto frontier. We then pivot to introducing Multi-Modal Optimization (MMO), which also requires "niching" methods to populate the different peaks of the optimization objective. We close by starting to set up background that motivates the particular designs of niche-preserving methods.
Whiteboard notes for this lecture can be found at:
https://www.dropbox.com/scl/fi/blmmcyw7e0uf2ivjh1lkk/IEE598-Lecture3D_4A-2026-03-03-From_Multi_Objective_to_Multi_Modal_Optimization-Notes.pdf?rlkey=q95a982to30ovnv6izej1cd5y&dl=0
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