Optimization and Simulation: Introduction to Simulation

Related lectures (32)

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Covers fundamental concepts of optimization and operations research, exploring real-world examples and key topics over a semester.

Covers scientific computing, process automation, and data management in computer science applications across different sectors.

Covers the Metropolis-Hastings algorithm and gradient-based approaches for biasing searches towards higher likelihood values.

Explores simulation of common structures and control of dynamic systems through friction and elasticity constants.

Explores VHDL for simulation, debugging, time modeling, event-based simulation, and testbench creation in digital system design.

Covers simulation, modeling, acceleration profiles, natural frequencies, rigidity calculations, and anti-resonance solutions for multi-axes robots.

By Prof. François Marechal covers the simulation and optimization of energy systems in industrial processes, waste, resources, and energy conversion.

Explores solving Connect Four using game theory algorithms and compares Alpha-Beta pruning with Monte-Carlo tree search.

Explores efficient stochastic numerical methods for modeling and learning, covering topics like the Analytical Engine and kinase inhibitors.

Explores the statistical analysis of turbulence, including Kolmogorov's theory and modeling methods.