I've created my implementation of genetic algorithm for knapsack problem to pass my University lecture.
If you are using python3.x just simply type below command to your shell:
python ./index.py- NumPy - to store knapsack and individuals inside Population,
- tqdm - to display progress bar,
- matplotlib - plots,
For defined list:
| No | Cost | Weight |
|---|---|---|
| 1 | 10 | 10 |
| 2 | 15 | 14 |
| 3 | 20 | 15 |
| 4 | 6 | 3 |
| 5 | 3 | 1 |
| 6 | 23 | 13 |
| 7 | 7 | 3 |
| 8 | 11 | 12 |
| 9 | 1 | 1 |
| 10 | 5 | 10 |
Configuration:
| Parameter | Value |
|---|---|
| Generation Number | 1000 |
| Population Size | 200 |
| Crossover Ratio | 90% |
| Mutation Ratio | 60% |
| Selection method | Roulette before 3/4 Generation, after that tournament |
| Crossover method | One Point Crossover |
| Mutation method | Bit Flip Mutation |
