Build@Mercari 2020 Week4 - Travelling Salesman PRoblem Challenges.

座標後tを8グループに分け、隣り合ったグループに最も近い点（ex.a_nearbとb_neara）を繋ぐ。同じグループの隣り合ったグループに近い点(ex.a_nearb, a_neare)の中点と、その中点からグループ内の最も遠い点(ex.farcitya)を結ぶ直線を引く。 図のように線を引く（a_neare →　直線の下側に存在する点 → farcitya →　直線の上側に存在する点 →　a_nearb）
その後2-opt法を使用する。

nが少ない時、グループに分けられないので、エラーが起こり、 エラーの度に、その穴をふさぐような対処をしてしまったため、コードが無駄に長く汚くなってしまった。

This is forked from https://github.com/hayatoito/google-step-tsp-2016.

1. 問題 巡回セールスマン問題 を解くアルゴリズムを考えてください。

2. 課題

このrepositoryを自分のgithubにforkして使ってください。 N = 5 から N = 2048までの７つの課題があります。

inputとoutputの形式については 3. Data Format Specification を見てください。

• 巡回セールスマン問題をとくアルゴリズムを考えて実装してください。
• solution_yours_{0-6}.csv をあなたのアルゴリズムでといた結果で上書きしてください。
• あなたの解法のpath lengthをscoreboardに書いてください

What matters in this optional task is your program's speed (execution time). The path length does not matter as long as it meets the condition. Your task is:

• Given input_6.csv, write a program which outputs a path shorter than 47,000

Input your program's execution time in the scoreboard. Faster (smaller) is better.

You can measure the execution time by time command.

$ time yourprogram input_6.csv solution_yours_6.csv
2.96s user 0.07s system 97% cpu 3.116 total

In this case, your score is 3.116 (s).

The demo page of the visualizer is: https://mercari-build.github.io/week4-tsp/visualizer/.

The assignment includes a helper Web page, visualizer/index.html, which visualizes your solutions. You need to run a HTTP server on your local machine to access the visualizer. Any HTTP server is okay. If you are not sure how to run a web server, use the following command to run the HTTP server included in the assignment. Make sure that you are in the top directory of the assignment before running the command.

./nocache_server.py # For Python 3
./nocache_server.py2.py # If you don’t want to install Python3

Then, open a browser and navigate to the http://localhost:8000/visualizer/. Note that visualizer was only tested by Google Chrome. Using the visualizer is up-to you. You don’t have to use the visualizer to finish the assignment. The visualizer is provided for the purpose of helping you understand the problem.

3. Data Format Specification

The input consists of N + 1 lines. The first line is always x,y. It is followed by N lines, each line represents an i-th city’s location, point xi,yi where xi, yi is a floating point number.

x,y
x_0,y_0
x_1,y_1
…
x_N-1,y_N-1

Output has N + 1 lines. The first line should be “index”. It is followed by N lines, each line is the index of city, which represents the visitation order.

index
v_0
v_1
v_2
…
v_N-1

Input Example:

x,y
214.98279057984195,762.6903632435094
1222.0393903625825,229.56212316547953
792.6961393471055,404.5419583098643
1042.5487563564207,709.8510160219619
150.17533883877582,25.512728869805677

Output (Solution) Example:

index
0
2
3
1
4

These formats are requirements for the visualizer, which can take only properly formatted CSV files as input.

5. What’s included in the assignment

To help you understand the problem, there are some sample scripts / resources in the assignment, including, but not limited to:

• solver_random.py - Sample stupid solver. You never lose to this stupid one.
• solution_random_{0-6}.csv - Sample solutions by solver_random.py.
• solver_greedy.py - Sample solver using the greedy algorithm. You should beat this definitely.
• solution_greedy_{0-6}.csv - Sample solutions by solver_greedy.py.
• solution_sa_{0-6}.csv - Yet another sample solutions. I expect all of you will beat this one too. The solver itself is not included intentionally.
• solution_wakanapo_{0-6}.csv - Sample solutions I solved when I was joined Google STEP 2016.
• solution_yours_{0-6}.csv - You should overwrite these files with your solution.
• solution_verifier.py - Try to validate your solution and print the path length.
• input_generator.py - Python script which was used to create input files, input_{0-6}.csv
• visualizer/ - The directory for visualizer.

6. Acknowledgments

この課題は私がgoogle step 2016に参加したときにやったものです。問題のわかりやすさ、visualizerによるアルゴリズムのみやすさ、楽しさなどにおいてこれを上回る課題はないと思ったので、Build@Mercariでも採用することにしました。