{"type":"ScholarlyArticle","title":"Placing Green Bridges Optimally, with Habitats Inducing Cycles","authors":[{"name":"Maike Herkenrath","slug":"maike-herkenrath","given":"Maike","family":"Herkenrath","affiliation":"Technische Universität Berlin , Faculty IV, Algorithmics and Computational Complexity , Germany"},{"name":"Till Fluschnik","slug":"till-fluschnik","given":"Till","family":"Fluschnik","affiliation":"Technische Universität Berlin , Faculty IV, Algorithmics and Computational Complexity , Germany"},{"name":"Francesco Grothe","slug":"francesco-grothe","given":"Francesco","family":"Grothe","affiliation":"Technische Universität Berlin , Faculty IV, Algorithmics and Computational Complexity , Germany"},{"name":"Leon Kellerhals","slug":"leon-kellerhals","given":"Leon","family":"Kellerhals","affiliation":"Technische Universität Berlin , Faculty IV, Algorithmics and Computational Complexity , Germany"}],"abstract":"Choosing the placement of wildlife crossings (i.e., green bridges) to reconnect animal species' fragmented habitats is among the 17 goals towards sustainable development by the UN. We consider the following established model: Given a graph whose vertices represent the fragmented habitat areas and whose weighted edges represent possible green bridge locations, as well as the habitable vertex set for each species, find the cheapest set of edges such that each species' habitat is connected. We study this problem from a theoretical (algorithms and complexity) and an experimental perspective, while focusing on the case where habitats induce cycles. We prove that the NP-hardness persists in this case even if the graph structure is restricted. If the habitats additionally induce faces in plane graphs however, the problem becomes efficiently solvable. In our empirical evaluation we compare this algorithm as well as ILP formulations for more general variants and an approximation algorithm with another. Our evaluation underlines that each specialization is beneficial in terms of running time, whereas the approximation provides highly competitive solutions in practice.","doi":"10.24963/ijcai.2022/531","url":"https://ijcai.org/proceedings/2022/531","pdf":"https://ijcai.org/proceedings/2022/0531.pdf","markdown":"https://ijcai.org/proceedings/2022/531.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/531","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":"Multidisciplinary Topics and Applications","track":"Main Track","number":531,"pages":{"first":3825,"last":3831},"keywords":["Multidisciplinary Topics and Applications: Computational Sustainability","Search: Combinatorial Search and Optimisation"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986921","length_sec":88,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38985064","length_sec":369,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Ament et al., 2014] R. 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