TSPSolvers

A common interface to a few solvers for the Traveling Salesman Problem: Concorde.jl, LKH.jl, TravelingSalesmanHeuristics.jl, and Hygese.jl.

To install:

] add TSPSolvers

Example

using TSPSolvers
M = [
    0  16   7  14
   16   0   3   5
    7   3   0  16
   14   5  16   0 
]
tour, tour_len = TSPSolvers.solve_tsp(M) 
# ([1, 3, 2, 4], 29)

The distance matrix M must be symmetric and integer-valued. It can be asymmetric for the LKH solver only. Note that the output tour does not repeat the first city at the end of the tour.

Also supports the TSPLIB input:

tour, tour_len = solve_tsp("gr17.tsp")

You can specify the algorithm and firstcity keywords:

tour, tour_len = TSPSolvers.solve_tsp(M; algorithm="FarthestInsertion", firstcity=2)
# ([2, 4, 1, 3], 29)

Supported algorithms are:

supported_algorithms = [
    "Concorde",             # Concorde.jl
    "LKH",                  # LKH.jl
    "HGS",                  # Hygese.jl
    "NearestNeighbor",      # TravelingSalesmanHeuristics.jl
    "FarthestInsertion",    # TravelingSalesmanHeuristics.jl
    "CheapestInsertion",    # TravelingSalesmanHeuristics.jl
    "TwoOpt",               # TravelingSalesmanHeuristics.jl
    "SimulatedAnnealing"    # TravelingSalesmanHeuristics.jl
]

You may also pass the solver-specific keyword arguments. For example:

tour, tour_len = TSPSolvers.solve_tsp(M; algorithm="LKH", INITIAL_TOUR_ALGORITHM="GREEDY", RUNS=5, TIME_LIMIT=10.0)
tour, tour_len = TSPSolvers.solve_tsp(M; algorithm="FarthestInsertion", do2opt=false)
tour, tour_len = TSPSolvers.solve_tsp(M; algorithm="SimulatedAnnealing", firstcity=3, steps=10, num_starts=3)
tour, tour_len = TSPSolvers.solve_tsp(M; algorithm="HGS", nbIter=100)

By default, nbIter is set to 4 * n for HGS.