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A small set of scala classes that solve a particular problem (double round robin tournament) through ACO (Ant Colony Optimization) and a bit of CP Constraint Processing

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readme.md

Scalants

Welcome to the Scalants project, mystery abounds...

Interesting results

For a reference, see the: Traveling Tournament Problem library

Classic N = 6 problem:

Done! Cost: 23916,000000, Optimal cost: 22969,000000, number of violations: 0, cost without violations: 23916,000000
0: [-5 3 -2 6 1 -4]
1: [-2 1 6 -5 4 -3]
2: [4 6 -5 -1 3 -2]
3: [3 -4 -1 2 -6 5]
4: [-6 -3 2 5 -4 1]
5: [-4 5 -6 1 -2 3]
6: [-3 4 1 -2 6 -5]
7: [6 -5 4 -3 2 -1]
8: [2 -1 5 -6 -3 4]
9: [5 -6 -4 3 -1 2]

Classic N = 8 problem:

Feasible Solution: 41505 (Easton June 4, 1999), 41113 (Easton Jan 27, 2000), 40416 (Cardemil, July 2 2002), 39947 (Zhang, August 19 2002), 39721 (Easton, August 25 2002) 
Lower Bound: 38760 (Trick Dec 15, 2000), 38870 (Easton Jan 2, 2001), 39479 (Easton Feb 26, 2002), 39721 (Irnich and Schrempp, June 24 2008)

Done! Optimal Cost: 40463,000000, Optimal cost: 39479,000000, number of violations: 0, cost without violations: 40463,000000
0: [5 4 6 -2 -1 -3 8 -7]
1: [7 6 4 -3 8 -2 -1 -5]
2: [8 -3 2 6 7 -4 -5 -1]
3: [-7 -6 -4 3 -8 2 1 5]
4: [-4 3 -2 1 -7 8 5 -6]
5: [-8 7 5 -6 -3 4 -2 1]
6: [6 -5 7 -8 2 -1 -3 4]
7: [2 -1 -8 7 6 -5 -4 3]
8: [-6 5 -7 8 -2 1 3 -4]
9: [-3 8 1 5 -4 7 -6 -2]
10: [-2 1 8 -7 -6 5 4 -3]
11: [4 -7 -5 -1 3 -8 2 6]
12: [3 -8 -1 -5 4 -7 6 2]
13: [-5 -4 -6 2 1 3 -8 7]

Done! Optimal Cost: 39461,975000, Optimal cost: 39479,000000, number of violations: 1, cost without violations: 38475,000000
0: [5 3 -2 6 -1 -4 8 -7]
1: [7 4 6 -2 8 -3 -1 -5]
2: [8 6 4 -3 7 -2 -5 -1]
3: [-7 -3 2 -6 -8 4 1 5]
4: [-8 7 -6 5 -4 3 -2 1]
5: [-4 5 7 1 -2 8 -3 -6]
6: [6 -7 -5 -8 3 -1 2 4]
7: [3 -8 -1 -7 6 -5 4 2]
8: [-6 -4 8 2 -7 1 5 -3]
9: [-3 8 1 7 -6 5 -4 -2]
10: [-2 1 5 8 -3 7 -6 -4]
11: [4 -5 -7 -1 2 -8 3 6]
12: [2 -1 -8 -5 4 -7 6 3]
13: [-5 -6 -4 3 1 2 -8 7]

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A small set of scala classes that solve a particular problem (double round robin tournament) through ACO (Ant Colony Optimization) and a bit of CP Constraint Processing

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