{"type":"ScholarlyArticle","title":"The COMPSET Algorithm for Subset Selection","authors":[{"name":"Yaniv Hamo","slug":"yaniv-hamo","given":"Yaniv","family":"Hamo","affiliation":""},{"name":"Shaul Markovitch","slug":"shaul-markovitch","given":"Shaul","family":"Markovitch","affiliation":""}],"abstract":"Subset selection problems are relevant in many domains. Unfortunately, their combinatorial nature prohibits solving them optimally in most cases. Local search algorithms have been applied to subset selection with varying degrees of success. This work presents COMPSET, a general algorithm for subset selection that invokes an existing local search algorithm from a random subset and its complementary set, exchanging information between the two runs to help identify wrong moves. Preliminary results on complex SAT, Max Clique, 0/1 Multidimensional Knapsack and Vertex Cover problems show that COMPSET improves the efficient stochastic hill climbing and tabu search algorithms by up to two orders of magnitudes.","doi":null,"url":"https://ijcai.org/proceedings/2005/213","pdf":"https://ijcai.org/proceedings/2005/0213.pdf","markdown":"https://ijcai.org/proceedings/2005/213.md","bibtex":"https://ijcai.org/proceedings/2005/bibtex/213","volume":{"slug":"2005","title":"Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2005","url":"https://ijcai.org/proceedings/2005/","year":2005,"location":"Edinburgh, Scotland, UK","dates":"","editors":"","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":213,"pages":{"first":728,"last":732},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}