Commit e8f05269 authored by Grégoire Grzeczkowicz's avatar Grégoire Grzeczkowicz
Browse files

More informations

parent fd0727fd
......@@ -123,15 +123,24 @@ Most exercises consists in adding a single function in an existing module
(or your own module) and use assemble it in the main executable.
1. Implement a simulated annealing.
You can use `num_simulated_annealing` or `bit_simulated_annealing` solver
2. Implement an evolutionary algorithm.
You can use `num_genetic` or `bit_genetic`
3. Implement an expected run time empirical cumulative density function.
You can execute `ert.py` which will plot 3 ert for two algorithms.
You can also use `draw_ert.py` with -N option for the number of run and optionally -v option to choose a target value (if not use will draw a surface for all target)
4. Implement a simple design of experiment to determine the best solver.
You can use `try_solver.py` to list the different parameter you want to try and get the best parameter (parameter inside the script)
5. Provide a solver for a competition.
For the competion, symply use my `snp.py`.
I have had the following penalisation to `num.py` :
......@@ -144,4 +153,3 @@ Most exercises consists in adding a single function in an existing module
if v >= domain_width:
s -= (v-domain_width)/domain_width
```
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment