{"type":"ScholarlyArticle","title":"HEA-D: A Hybrid Evolutionary Algorithm for Diversified Top-k Weight Clique Search Problem","authors":[{"name":"Jun Wu","slug":"jun-wu","given":"Jun","family":"Wu","affiliation":"Information Science and Technology , Northeast Normal University , China"},{"name":"Chu-Min Li","slug":"chu-min-li","given":"Chu-Min","family":"Li","affiliation":"MIS , Universitéde Picardie Jules Verne , France"},{"name":"Yupeng Zhou","slug":"yupeng-zhou","given":"Yupeng","family":"Zhou","affiliation":"Information Science and Technology , Northeast Normal University , China"},{"name":"Minghao Yin","slug":"minghao-yin","given":"Minghao","family":"Yin","affiliation":"Information Science and Technology , Northeast Normal University , China; Key Laboratory of Applied Statistics of MOE , Northeast Normal University , China"},{"name":"Xin Xu","slug":"xin-xu","given":"Xin","family":"Xu","affiliation":"Information Science and Technology , Northeast Normal University , China"},{"name":"Dangdang Niu","slug":"dangdang-niu","given":"Dangdang","family":"Niu","affiliation":"College of Information Engineering , Northwest A&F University , China"}],"abstract":"The diversified top-k weight clique (DTKWC) search problem is an important generalization of the diversified top-k clique (DTKC) search problem with extensive applications, which extends the DTKC search problem by taking into account the weight of vertices. In this paper, we formulate DTKWC search problem using mixed integer linear program constraints and propose an efficient hybrid evolutionary algorithm (HEA-D) that combines a clique-based crossover operator and an effective simulated annealing-based local optimization procedure to find high-quality local optima. The experimental results show that HEA-D performs much better than the existing methods on two representative real-world benchmarks.","doi":"10.24963/ijcai.2022/668","url":"https://ijcai.org/proceedings/2022/668","pdf":"https://ijcai.org/proceedings/2022/0668.pdf","markdown":"https://ijcai.org/proceedings/2022/668.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/668","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Search","track":"Main Track","number":668,"pages":{"first":4821,"last":4827},"keywords":["Search: Heuristic Search","Search: Local search","Search: Evolutionary Computation","Search: Combinatorial Search and Optimisation"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986472","length_sec":72,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38984615","length_sec":316,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Berry et al., 2004] Nina Berry, Teresa Ko, Tim Moy, Juli- enne Smrcka, Jessica Turnley, and Ben Wu. 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