{"title":"Optimal Area Polygonization by Triangulation and Visibility Search","authors":"Julien Lepagnot, L. Moalic, Dominique Schmitt","doi":"10.1145/3503953","DOIUrl":null,"url":null,"abstract":"The aim of the “CG:SHOP Challenge 2019” was to generate optimal area polygonizations of a planar point set. We describe here the algorithm that won the challenge. It is a two-phase algorithm based on the node-insertion move technique, which comes from the TSP. In the first phase, we use constrained triangulations to check efficiently the simplicity of the generated polygonizations. In the second phase, we perform visibility searches to be able to generate a wider variety of polygonizations. In both phases, the simulated annealing metaheuristic is implemented to approach the optimum.","PeriodicalId":53707,"journal":{"name":"Journal of Experimental Algorithmics","volume":" ","pages":"1 - 23"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Experimental Algorithmics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3503953","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 1
Abstract
The aim of the “CG:SHOP Challenge 2019” was to generate optimal area polygonizations of a planar point set. We describe here the algorithm that won the challenge. It is a two-phase algorithm based on the node-insertion move technique, which comes from the TSP. In the first phase, we use constrained triangulations to check efficiently the simplicity of the generated polygonizations. In the second phase, we perform visibility searches to be able to generate a wider variety of polygonizations. In both phases, the simulated annealing metaheuristic is implemented to approach the optimum.
期刊介绍：
The ACM JEA is a high-quality, refereed, archival journal devoted to the study of discrete algorithms and data structures through a combination of experimentation and classical analysis and design techniques. It focuses on the following areas in algorithms and data structures: ■combinatorial optimization ■computational biology ■computational geometry ■graph manipulation ■graphics ■heuristics ■network design ■parallel processing ■routing and scheduling ■searching and sorting ■VLSI design
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