Explore the fascinating world of simulated annealing in this 28-minute RubyConf 2022 talk by Chris Bloom. Dive into the metallurgy-inspired algorithm designed to find near-optimal solutions for constrained optimization problems. Learn about the algorithm's real-world applications, understand what constitutes a constrained optimization problem, and discover why "good enough" solutions are sometimes preferable. Gain insights into implementing simulated annealing in Ruby applications using the Annealing gem. Follow along as the speaker breaks down complex concepts, including optimization problems, the Traveling Salesperson Problem (TSP), and its metal band variant. Examine the simulated annealing process step-by-step, from defining an annealing schedule to measuring energy states and deciding on optimal arrangements.
Simulated Annealing: The Most Metal Algorithm Ever - Lecture
Overview
Syllabus
Intro
Optimization problems
Traveling Salesperson Problem (TSP)
Traveling Metal Band Problem (TSP)
Traveling Metal Band Problem Alternative Version
Meeting cost matrix
The simulated annealing process
Define an annealing schedule
Select an initial arrangement
Generate a new state
Measure the energy of both states
Decided which state to keep
Check if the simulation is done
Taught by
Confreaks
