Supplemental visualizations for Theodore Pavlic's IEE/CSE 598: Bio-Inspired AI and Optimization at Arizona State University.
Lectures and other helpful short video tutorials can be found at TedPavlic's YouTube channel.
Step through the annealing process: temperature schedules, neighbor selection, and probabilistic acceptance criteria on an energy landscape.
Run parallel fixed-temperature SA replicas at different temperatures and periodically swap configurations between them — high-temperature replicas explore globally while low-temperature ones refine solutions.
Walk through Sewall Wright's three-phase Shifting Balance Theory: how genetic drift, selection, and interdemic migration help a metapopulation escape local fitness peaks.
Watch animals distribute across resource patches to equalize individual fitness — a behavioral ecology result that motivates fitness sharing in multi-modal genetic algorithms.
Selection and drift purge diversity; mutation replenishes it. This figure frames the four forces of evolution as a field pushing populations toward fixation, motivating how to tune GA hyperparameters for a gradual shift from exploration to exploitation.