The challenge consisted of two evaluations, one online where teams continuously submitted their solutions to a set of 50 instances, and a final evaluation where each team's code was evaluated in a consistent environment on 50 new unseen instances.
The rankings from the public leaderboard are show in the table below. More detailed information is available.
|1||SENCOM||CODeS, KU Leuven||0.75|
|2||OptaPlanner Delirium||Red Hat and unaffiliated||9.99|
|3||Kadioglu, Pacino, Tierney||Mixed||34.87|
|icon||Deepak Mehta||Insight, UCC||35.34|
|icon||KULZ||DTAI, KU Leuven||50.37|
|icon||Team Prolog||Insight, UCC||76.42|
Longest Period on Top
Teams were encourages to submit regularly to the public leaderboard, the prize for the longest period in first position goes to team SENCOM.
|Team Name||Time at the top|
|1||SENCOM||54 days, 23:53:55|
|2||OptaPlanner Delirium||1 day, 21:51:52|
|3||Deepak Mehta||1 day, 5:06:16|
A visualization of each team's score over time.
Final Evaluation Leaderboard
1st place goes to team SENCOM from CODeS, KU Leuven. Tony Wauters, David Van Den Dooren, Thomas Sys
|1||SENCOM||CODeS, KU Leuven||3.87|
|2||OptaPlanner Delirium||Red Hat and unaffiliated||26.13|
|icon||KULZ||DTAI, KU Leuven||45.18|
|3||Kadioglu, Pacino, Tierney||Mixed||60.37|
Penalty of Forecasted Energy Price
The ultimate goal of the challenge is to investigate the penalty of scheduling with a forecasted energy price, and to develop improvements to this either by producing a better forecast or by adapting the scheduling task. The plot below shows that two completely different schedules are produced if we schedule with the forecasted energy price (blue) or with the actual price data (red).