The report is located at bohacek_frantisek_report.pdf, it has
been generated from report.md

Rust has been used to write the library and program for solving
constrained problems. Cargo is used for managing the dependencies.

# How to run

To run the tsp, go into the constr_hw02 folder, ie. `cd tsp_hw01`,
then use `cargo run --release -- srank|moe problem`,
Supported problems are: `g06`, `g08`, `g11`, `g24`.

So for example: `cargo run --release -- srank g06`

# Solutions

The solution is then saved to `constr_hw01/solutions/<instance>`,
csv file with best candidate fitness (only feasible candidates
can be saved) and next to it is file with faction of feasible
candidates in each iteration.

# Plotting

The solutions might be plotted by using `tsp_plotter` program.
`cd tsp_plotter` and then `cargo run --release -- <feature>`,
where feature is one of:
```
```
The features are hardcoded in the code and used in the report,
they say what algorithms and instances should be used in a given plot.
They are taken from the `constr_hw02` folder.

The name of the plotter is same as used for hw01 as the plotting itself is the same.

# 'Reproducing' the plots in the report

To obtain the graphs in the report, use the following sequence of commands:

1. `compute.sh` to compute all the algorithms on all instances, 10 times for each instance.
2. Generate the plots, go to `py_plotter` folder, and run
```
python3 ./plotter.py config_feasible_g11.json
python3 ./plotter.py config_feasible_g06.json
python3 ./plotter.py config_feasible_g05.json
python3 ./plotter.py config_best_g09.json
```

Now all the csv solutions are in `constr_hw01/solutions` and all the plots are in
`tsp_plotter/plots`

The graphs won't be 1:1, because randomness is involved and the seeds haven't been captured
and aren't configurable.