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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the concepts of optimization and simulation, focusing on techniques such as lexicographic rules, constrained optimization, and heuristics. The instructor explains the main differences between single-objective and multi-objective optimization, emphasizing the importance of maintaining a set of potential Pareto optimal solutions. Through examples like the priced knapsack problem and local search algorithms, the lecture illustrates how these techniques are applied in practice. The Variable Neighborhood Search method is also discussed, highlighting the significance of exploring different neighborhood sizes to find Pareto solutions. The lecture concludes by emphasizing the need for trade-offs in problem-solving and the concept of Pareto frontier.