ACP Challenge - Ranking

Final Global Ranking (August 20, 2016)

Teams are ranked based on the sum of normalized gain across all the instances (normalization is done with reference to best gain on each instance). Thus for each instance the contribution of one instance to their global gain is between 0 and 1 (1 if the team obtain the best solution for this instance).

Global Ranking
# Global Teams
1 6.000000000 Top Steel, TorpedoOptimizers (ex aequo)
3 5.999996464 Martin J. Geiger
4 5.999996408 Eaglet Smelters
5 5.999975286 Octopus
6 5.965980375 organiser

Final Temporal Ranking (August 20, 2016)

Here, Teams are ranked based on number of days where they are ranked first in Global Ranking above (from July 4, 2016 to August 20, 2016).

Temporal Ranking
#days Name
47 TorpedoOptimizers
3 Top Steel
1 Martin J. Geiger

Global Ranking (current but challenge is off)

Teams are ranked based on the sum of normalized gain across all the instances (normalization is done with reference to best gain on each instance). Thus for each instance the contribution of one instance to their global gain is between 0 and 1 (1 if the team obtain the best solution for this instance).

Global Ranking
# Global Teams
1 6.000000000 Top Steel, TorpedoOptimizers (ex aequo)
3 5.999999290 Octopus
4 5.999996464 Martin J. Geiger
5 5.999996408 Eaglet Smelters
6 5.999750298 EdonGashi
7 5.965980375 organiser

Temporal Ranking (current but challenge is off)

Here, Teams are ranked based on number of days where they are ranked first in Global Ranking above (since July 4, 2016).

Temporal Ranking
#days Name

Ranking by Instance (current but challenge is off)

Since the objective function is lexicographic, the second objective (timeDesulf) will be normalized to have a value always between 0 and 1. In the output of the checker you’ll see:

cost = torpedo + timeDesulf / (upperBoundTorpedo * durDesulf)

The ranking is based on this cost. More precisely it is on the gain with reference to a solution (worst solution) that would use one torpedo for every order at the BF:

gain = (maxNumberTorpedo + 1) - cost
Ranking for instance instance01.ins (download)
# Gain Teams
1 846.910937500 TorpedoOptimizers, Top Steel (ex aequo)
3 846.910625000 Octopus
4 846.910312500 Eaglet Smelters
5 846.910000000 Martin J. Geiger
6 846.845937500 EdonGashi
7 835.249699074 organiser
Ranking for instance instance02.ins (download)
# Gain Teams
1 1496.913928571 TorpedoOptimizers, Top Steel, Octopus (ex aequo)
4 1496.912678571 Martin J. Geiger
5 1496.912321429 Eaglet Smelters
6 1496.823928571 EdonGashi
7 1484.578425325 organiser
Ranking for instance instance03.ins (download)
# Gain Teams
1 2197.870714286 TorpedoOptimizers, Top Steel, Octopus (ex aequo)
4 2197.870595238 Eaglet Smelters
5 2197.869880952 Martin J. Geiger
6 2197.812619048 EdonGashi
7 2185.454038095 organiser
Ranking for instance instance04.ins (download)
# Gain Teams
1 997.843000000 TorpedoOptimizers, Martin J. Geiger, Top Steel, Octopus, Eaglet Smelters (ex aequo)
6 997.842500000 EdonGashi
7 997.842250000 organiser
Ranking for instance instance05.ins (download)
# Gain Teams
1 1796.915168539 TorpedoOptimizers, Top Steel, Octopus (ex aequo)
4 1796.913904494 Martin J. Geiger, Eaglet Smelters (ex aequo)
6 1796.830337079 EdonGashi
7 1790.741130878 organiser
Ranking for instance instance06.ins (download)
# Gain Teams
1 2496.925000000 TorpedoOptimizers, Top Steel (ex aequo)
3 2496.924148936 Octopus
4 2496.923723404 Martin J. Geiger
5 2496.922446809 Eaglet Smelters
6 2496.828404255 EdonGashi
7 2489.624526112 organiser

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New A CP 2016 Google photo album is available

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CP 2016 Accepted Papers

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