Made Indrayana Putra, Muhammad Arzaki, G. Wulandari
{"title":"Solving Yin-Yang Puzzles Using Exhaustive Search and Prune-and-Search Algorithms","authors":"Made Indrayana Putra, Muhammad Arzaki, G. Wulandari","doi":"10.12962/j24775401.v8i2.13720","DOIUrl":null,"url":null,"abstract":"—We investigate some algorithmic and mathematical aspects of Yin-Yang/Shiromaru-Kuromaru puzzles. Specifically, we discuss two algorithms for solving arbitrary Yin-Yang puzzles, namely the exhaustive search approach and the prune-and-search technique. We show that both algorithms have an identical asymptotic running time of O (max { mn, 2 mn − h } ) for finding all solutions of a Yin-Yang instance with h hints of size m × n . Nevertheless, our experiments show that the practical running time of the prune-and-search technique outperforms the conventional exhaustive search approach.","PeriodicalId":357596,"journal":{"name":"International Journal of Computing Science and Applied Mathematics","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computing Science and Applied Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12962/j24775401.v8i2.13720","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
—We investigate some algorithmic and mathematical aspects of Yin-Yang/Shiromaru-Kuromaru puzzles. Specifically, we discuss two algorithms for solving arbitrary Yin-Yang puzzles, namely the exhaustive search approach and the prune-and-search technique. We show that both algorithms have an identical asymptotic running time of O (max { mn, 2 mn − h } ) for finding all solutions of a Yin-Yang instance with h hints of size m × n . Nevertheless, our experiments show that the practical running time of the prune-and-search technique outperforms the conventional exhaustive search approach.