Commit 92975345 authored by Grégoire Grzeczkowicz's avatar Grégoire Grzeczkowicz
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parent 451de15a
...@@ -123,8 +123,13 @@ Most exercises consists in adding a single function in an existing module ...@@ -123,8 +123,13 @@ Most exercises consists in adding a single function in an existing module
(or your own module) and use assemble it in the main executable. (or your own module) and use assemble it in the main executable.
1. Implement a simulated annealing. 1. Implement a simulated annealing.
You can use num_simulated_annealing or bit_simulated_annealing solver
2. Implement an evolutionary algorithm. 2. Implement an evolutionary algorithm.
You can use num_genetic or bit_genetic
3. Implement an expected run time empirical cumulative density function. 3. Implement an expected run time empirical cumulative density function.
You can call draw_ert.py with -N option for the number of run and -v option to choose a target value
4. Implement a simple design of experiment to determine the best solver. 4. Implement a simple design of experiment to determine the best solver.
You can use try_solver to list the different parameter you want to try and get the best parameter
5. Provide a solver for a competition. 5. Provide a solver for a competition.
For the competion, symply use my num_greedy
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