Pruthviraj Gojare — R23-T049: Trace genetic_algorithm/travelling_salesman_problem.py step by step #50

Student: Pruthviraj Gojare

Task: R23-T049 · 9 of 10
Repository: https://github.com/S-AI-Projects/TheAlgorithms-Python
Assigned working branch: student/e26b07f0834

Goal

Use a debugger to watch the algorithm run on a small input, and turn your observations into documentation and a test. Fix the random seed and trace one generation: population, fitness values, selection and crossover results.

Steps

1. Choose a small input (from a doctest or your own) and step through with python -m pdb or breakpoint(); record the key variables at each step.
2. Write work/R23-T049/TRACE.md as a table of steps and variable values.
3. Turn one observation into a new doctest (e.g. an intermediate value or an edge case you discovered).
4. Explain one thing that surprised you.
5. Make the code change in the repository: genetic_algorithm/travelling_salesman_problem.py: a seeded doctest for one generation step based on your trace. Re-run the automated check and the repo's own tests afterwards.
6. Prepare the PR: on branch R23-T049, commit the code change plus your work/R23-T049/ evidence, put your findings in the PR description and open the PR against the org fork. For a later upstream PR, create a second branch containing only the code change (no work/ folder).

Done when

☐ TRACE.md (fixed seed) records one generation: population, fitness values, chose_ts/chose_rws selections, crossing and mutate results.
☐ genetic_algorithm/travelling_salesman_problem.py gains a seeded doctest for one generation step based on the trace.
☐ Existing 39 doctests pass.

Submission checklist

• Complete this task and its checks.
• Add the required evidence and link your pull request here.
• Select this S-AI-Projects fork as the PR base repository.
• Request instructor review.

Keep this PR focused on this task. Do not submit assignment PRs to the upstream repository.