Reference no: EM131076807
Project: The Travelling Salesman Problem (TSP)
Project Specification
Your group will design and implement an algorithm (or algorithms) for finding the best tour you can. TSP is not a problem for which you will be able to easily find optimal solutions. It is difficult. Your goal is to find the best solution you can in a certaintime frame. You may want to start with some local search heuristics. There is much literature on methods to "solve" TSP please cite any sources you use. Use any programming language you want that runs on flip2.engr.oregonstate.edu.
Your program must:
• Accept problem instances on the command line
• Name the output file as the input file's name with .tour appended (for example input
tsp_example_1.txt will output tsp_example_1.txt.tour)
• Compile/Execute correctly and without debugging on flip2.engr.oreognstate.eduaccording to specifications and any documentation you provide.
Input specifications:
• A problem instance will always be given to you as a text file.
• Each line defines a city and each line has three numbers separated by white space.
o The first number is the city identifier
o The second number is the city's x-coordinate
o The third number is the city's y-coordinate.
Output specifications:
• You must output your solution into another text file with n + 1 line, where n is the number of cities.
• The first line is the length of the tour your program computes.
• The next n lines should contain the city identifiers in the order they are visited by your tour.
o Each city must be listed exactly once in this list.
o This is the certificate for your solution and your solutions will be checked. If they are not valid you will not receive credit for them.
Example instances: We have provided you with three example instances. They are available on Canvas and are provided according to the input specifications.
• tsp_example_[*].txt Input files
• tsp_example_[*].txt.tour Example outputs corresponding to these three input cases. The optimal tour lengths for example instances 1, 2, and 3 are 108159, 2579 and 1573084, respectively. Clearly these do not match the values in the tour files. You should use these values to evaluate your algorithm. For full credit it is required that the ratio of
(Your solution)/(optimal solution) <= 1.25.
Testing
A testing procedure tsp-verifier.py is given that we will use to verify your solutions. Usage to test example an instance is: (NOTE: requires TSPAllVisitied.py)
python tsp-verifier.py inputfilename solutionfilename
You should test that your outputs are correct. By "correct" we mean that the distances have been computed correctly not that the solution is optimal.
Competition
We will hold a completion. The competition will require your program to find the best solution possible to one or more test instances within a fixed amount of time (e.g. 3 minutes). The competition instances will be available on Monday 5/30/16 at 8:00 am PST. You will not be told the optimal tour length for these instances. You will post your results to the competition instances tothe competition discussion board.
Project Report
You will submit a project report containing the following:
• A description of at least three different methods/algorithms for solving the Traveling Salesman Problem. Summarize any research you did.
• A verbal description of your algorithm(s) as completely as possible. You may select more than one algorithm to implement.
• A discussion on why you selected the algorithm(s).
• Pseudo code
• Your "best" tours for the three example instances and the time it took to obtain these tours.
• Your best tours for the competition test instance(s).