Lecture
Optimization and Simulation
Related lectures (33)
Optimization and Simulation
Covers optimization and simulation techniques for drawing from multivariate distributions and dealing with correlations.
Simulation & Optimization: Poisson Process & Random Numbers
Explores simulation pitfalls, random numbers, discrete & continuous distributions, and Monte-Carlo integration.
Markov Chains and Algorithm Applications
Covers the application of Markov chains and algorithms for function optimization and graph colorings.
Optimisation in Energy Systems
Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
Optimization Methods: Theory Discussion
Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.
Markov Chains: Simulation and Optimization
Explores Markov chains, Metropolis-Hastings, and simulation for optimization purposes, highlighting the significance of ergodicity in efficient variable simulation.
Thermodynamic Properties: Equations and Models
Explains thermodynamic properties, equations of state, and mixture rules for energy systems modeling.
Markov Chains and Algorithm Applications
Covers Markov chains and their applications in algorithms, focusing on Markov Chain Monte Carlo sampling and the Metropolis-Hastings algorithm.
Traveling Salesman Problem: Introduction and Approximation Methods
Introduces the Traveling Salesman Problem and explores approximation methods using Markov chains.
Monte Carlo Chain: Motivation and Algorithm
Explores the motivation and algorithm behind the Monte Carlo Chain method.