Optimization and Simulation: Simulated Annealing

This lecture covers the concept of simulated annealing, a heuristic optimization technique inspired by metallurgy, where the objective function can both decrease and increase during the search process. Starting with high temperature for flexibility, the method progressively reduces the temperature to find the optimal solution. Practical aspects such as parameter tuning and neighborhood structure exploration are discussed, along with the importance of diversification to escape local minima. The lecture also introduces meta-heuristics like variable neighborhood search and bio-inspired methods such as genetic algorithms and ant colony optimization.