{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T16:46:03Z","timestamp":1770914763864,"version":"3.50.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>Integer programming (IP) is widely used within operations research to model and solve complex combinatorial problems such as personnel rostering and assignment problems.  Modelling such problems is difficult  for  non-experts  and  expensive  when  hiring domain experts to perform the modelling.  For many  tasks,  however,  examples  of  working  solutions are readily available.  We propose ARNOLD, an approach that partially automates the modelling step  by  learning  an  integer  program  from  example  solutions. Contrary  to  existing  alternatives, ARNOLD natively handles multi-dimensional quantities  and  non-linear  operations,  which  are  at  the core of IP problems, and it only requires examples of feasible solution.  The main challenge is to efficiently  explore  the  space  of  possible  programs. Our  approach  pairs  a  general-to-specific  traversal strategy with a nested lexicographic ordering in order to prune large portions of the space of candidate  constraints  while  avoiding  visiting  the  same candidate multiple times. Our empirical evaluation shows that ARNOLD can acquire models for a number of realistic benchmark problems<\/jats:p>","DOI":"10.24963\/ijcai.2019\/158","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:46:05Z","timestamp":1564285565000},"page":"1130-1136","source":"Crossref","is-referenced-by-count":4,"title":["Acquiring Integer Programs from Data"],"prefix":"10.24963","author":[{"given":"Mohit","family":"Kumar","sequence":"first","affiliation":[{"name":"KU Leuven"}]},{"given":"Stefano","family":"Teso","sequence":"additional","affiliation":[{"name":"KU Leuven"}]},{"given":"Luc","family":"De Raedt","sequence":"additional","affiliation":[{"name":"KU Leuven"}]}],"member":"10584","event":{"name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","theme":"Artificial Intelligence","location":"Macao, China","acronym":"IJCAI-2019","number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2019,8,10]]},"end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:47:12Z","timestamp":1564285632000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/158"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/158","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}