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1
Intro
2
Optimization problems
3
Traveling Salesperson Problem (TSP)
4
Traveling Metal Band Problem (TSP)
5
Traveling Metal Band Problem Alternative Version
6
Meeting cost matrix
7
The simulated annealing process
8
Define an annealing schedule
9
Select an initial arrangement
10
Generate a new state
11
Measure the energy of both states
12
Decided which state to keep
13
Check if the simulation is done
Description:
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

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