M2 AIC: Advanced Optimization


Université Paris-Saclay, Nov. 2016 - Feb. 2017

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Exercises


During the course, you will find here the documents for the theoretical and practical exercises.


November 22, 2016 - Pure Random Search and (1+1)EA on ONEMAX

The Pure Random Search (PRS) and the (1+1)EA are some of the simplest randomized search heuristics which are simple enough to understand their behaviour theoretically on simple functions. In this exercise, we investigate their ability to optimize the ONEMAX function---both experimentally and theoretically.


Exercise sheet

November 29, 2016 - An Evolutionary Algorithm for the TSP

The goal of this exercise is to showcase how easy it is to implement an evolutionary algorithm from scratch for the traveling salesperson problem (TSP) and understand its basic working principles and their influence on the algorithm performance.


Exercise sheet

December 6, 2016 - Continuous Optimization

This exercise consists of three theoretical questions around continuous optimization.


Exercise sheet

January 3, 2017 - Continuous Optimization II

This exercise revisits the Covariance Matrix Adaptation Evolution Strategy (CMA-ES).


Exercise sheet

January 31, 2017 - Weighted Sum on COCO

In this exercise, we plan to implement a simple weighted sum and benchmark it on the bbob-biobj-ext suite of the COCO platform.


Python skeleton of example experiment

Last updated: Mon, 30 Jan 2017 22:56