Design Optimization: Principles and Applications

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Related lectures (30)

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Optimisation Strategies: Energy Systems Modelling and Optimization

Explores solving strategies for energy system optimization problems and different types of optimization approaches.

Optimization Techniques: Local Search, VNS, Simulated Annealing

Explores optimization techniques like local search, VNS, and simulated annealing.

Optimization and Simulation

Explores optimization techniques like Metropolis-Hastings and Simulated Annealing through Markov chains and stationary distributions.

Multi-Objective Optimization: Methods & Solutions

Explores key performance indicators, multi-objective optimization, and heuristic methods for reaching optimum solutions.

Optimization and Simulation

Covers optimization and simulation techniques for drawing from multivariate distributions and dealing with correlations.

Energy optimization strategies

Covers brainstorming options for smart operation changes, heat recovery, and PV panel performance.

Stochastic Gradient Descent: Non-convex Optimization Techniques

Discusses Stochastic Gradient Descent and its application in non-convex optimization, focusing on convergence rates and challenges in machine learning.

Optimization in Engineering

Explores optimization methods in engineering, covering decision variables, constraints, and various solving techniques.

MILP Model and Typical Days by FM

Discusses MILP model, typical days, clustering, and extreme periods analysis in energy systems optimization.

Set Cover: Integrality Gap

Explores the integrality gap concept in set cover and multiplicative weights algorithms.