{"type":"ScholarlyArticle","title":"A Novel Local Search Algorithm for the Vertex Bisection Minimization Problem","authors":[{"name":"Rui Sun","slug":"rui-sun","given":"Rui","family":"Sun","affiliation":""},{"name":"Xinyu Wang","slug":"xinyu-wang","given":"Xinyu","family":"Wang","affiliation":""},{"name":"Yiyuan Wang","slug":"yiyuan-wang","given":"Yiyuan","family":"Wang","affiliation":""},{"name":"Jiangnan Li","slug":"jiangnan-li","given":"Jiangnan","family":"Li","affiliation":""},{"name":"Yi Zhou","slug":"yi-zhou","given":"Yi","family":"Zhou","affiliation":""}],"abstract":"The vertex bisection minimization problem (VBMP) is a fundamental graph partitioning problem with numerous real-world applications. In this study, we propose a (k, l, S)-cluster guided local search algorithm to address this challenge.\r\nFirst, we propose a novel (k,l,S)-cluster enumeration procedure, which is based on two key concepts: the (k, l, S)-cluster and the local cluster core. The (k, l, S)-cluster limits both the connectivity and distinct boundaries of a given vertex set, and the local cluster core represents the most cohesive substructure within a (k, l, S)-cluster. Building up on the above (k, l, S)-cluster enumeration procedure, we present a novel (k, l, S)-cluster guided perturbation mechanism designed to escape from local optima. \r\nNext, we propose a two-manner local search procedure that employs two distinct search models to explore the neighboring search space efficiently. Experimental results demonstrate that the proposed algorithm performs best on nearly all instances.","doi":"10.24963/ijcai.2025/996","url":"https://ijcai.org/proceedings/2025/996","pdf":"https://ijcai.org/proceedings/2025/0996.pdf","markdown":"https://ijcai.org/proceedings/2025/996.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/996","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Search","track":"Main Track","number":996,"pages":{"first":8956,"last":8965},"keywords":["Search: S: Heuristic search","Search: S: Local search"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}