Traveling Salesman added to Vault

[glennpat]

Traveling Salesman is showing up in the Vault today. A created a team on the project a couple of months ago, but only did a few WUs. I just added more boxes on it, but have not received any work yet.

Link to project http://bob.myisland.as/tsp/

[Paladin]

Hurray, another Vault project that doesn't actually distribute any work units.
http://bob.myisland.as/tsp/forum_thread.php?id=142

Guess the Salesman also sells vacuum cleaners that don't suck?

[glennpat]

Doesn't look good in getting work units for awhile. Looks like the project is in transition to a new algorithm. Hopefully it will be working soon.

[[XC] riptide]

Boinc Project.

Just also for the readers I'll add in the description.

About TSP
The Traveling Salesman Problem (TSP) is not hard to explain. For a given set of cites, visit each city once (once and only once) and minimize the distance you travel. This deceptively simple problem is trivial given a small set of cities, however, as you add more cities the number of possible paths goes through the roof. It should come as no surprise that the TSP is classified as an NP-Hard problem, with the number of Hamiltonian paths being equal to n!/2 where n is equal to the number of cities in the problem.
Who cares about traveling salesmen? Do we really need to know how to get a traveling salesman to our door in the shortest time? No, but generic forms of the TSP have been used in laying out circuit boards to insure time signals remain constant, cutting raw materials (i.e. lumber or sheet metal) to minimize waste, clustering data arrays, analyzing crystal structures, scheduling and much more.

An efficient general solution has not been found. Mathematicians have decided that the best case scenario is an algorithm that has a polynomial variation with respect to the number of cites. The best solutions to date vary exponentially with respect to the number of cites. This is where the BOINC project TSP comes in. The TSP project is undertaking the arduous task of using the brute force method to find an optimal solution to a 48 city TSP. Once the optimal path(s) is/are known evaluation of other algorithms can begin. The final step for the TSP is to determine if a compbination of algorithms can produce results quicker. For example, use a genetic algorithm to seed the first path in a branch and bound search. Future algorithms include genetic algorithms, repetitive nearest neighbor, simulated annealing and ant colony optimization.

TSP is based at the American Samoa Hibiscus House.

[Paladin]

Sure seems a lot longer than 2-weeks since this dead project was Vault'ed. So far it's done nothing but immitate APS@Home when it was similarly (mis)Vault'ed.

No updates on the project's web site either.

[glennpat]

There is a thread about it's removal from the vault:


http://www.team-ninja.com/vbulletin/showthread.php?t=43305

Hopefully it will get removed.

[glennpat]

Traveling Salesman has been removed from the Vault. :clap: