Metaheuristic

Related lectures (22)

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Introduces the course syllabus, grading scheme, and classical and quantum computation models.

Explores optimization techniques in engineering for solving complex problems efficiently.

Explores optimization and simulation techniques, emphasizing heuristics intensification for efficient solution finding.

Covers the Curie-Weiss model in Statistical Physics, including magnetization probability, free entropy, and the cavity method.

Covers the application of Markov chains and algorithms for function optimization and graph colorings.

Covers the formulation of constraint satisfaction problems and systematic algorithms for solving them efficiently.

Covers Bayes estimator, Simulated Annealing, and EM for parameter estimation.

Covers the concept of Gibbs sampling and its application in simulated annealing.

Explains thermodynamic properties, equations of state, and mixture rules for energy systems modeling.

Explores heuristic-based optimization using the INGRES database system example.