Solving the travelling salesman problem with ant colony optimization
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TravellingAnts is an implementation of the Ant Colony metaheuristic optimization algorithm (specifically, Ant System) for solving the travelling salesmen problem.

The repository includes a library for solving arbitrary graphs and also includes a specific example.

The code is intended to be clear and modular. Ants are launched concurrently to improve execution speed. The solver provides call-backs for listening to the running computation rather than hard-coding loggers.

Sample run

A comparison of the mean cost of each ant's solution per iteration to the overal cumulative best solution as the algorithm progress:

Sample iterations

The best solution from the run above:

Sample solution


TravellingAnts is written in Scala. It requires that sbt is installed.

To execute the solver on the example solution and save the solution in the DOT format, execute:

$ sbt --warn run >

Intermediate progress is printed to the standard error device (stderr) and also to a log file (travelling-ants.log) in comma-separated value (CSV) format suitable for analysis.

To produce a visual image of the resulting solution, you can use neato from the grapviz suite of programs:

$ neato -Tpng > output.png