{"title":"遗传算法在北干巴鲁市旅游路线优化中的应用","authors":"Eri Yanto, Ramalia Noratama Putri","doi":"10.35145/jabt.v1i1.22","DOIUrl":null,"url":null,"abstract":"The number of tourist attractions that are not yet well known, reinforced by the release of Pekanbaru City Government data that the tourism sector only accounts for about 0.9% of the national tourism sector. Therefore, this study aims to optimize the determination of Pekanbaru city tourist travel routes by using genetic algorithms or Genetic Algorithms. Genetic algortima process generally consists of several stages, starting from the initial generation, determination of fitness, crossover stage, mutation to the generation of advanced stages. With an accuracy rate of the best offered solutions reaching around 88% and an average solution search of about 19 seconds per iteration on a constant 100x trial, the results of this study can be used to help general users or Tour & Travel businesses in determining travel routes more optimal travel and a better travel experience.","PeriodicalId":224855,"journal":{"name":"Journal of Applied Business and Technology","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"APPLICATION OF GENETIC ALGORITHM IN TOURISM ROUTE OPTIMIZATION IN PEKANBARU CITY\",\"authors\":\"Eri Yanto, Ramalia Noratama Putri\",\"doi\":\"10.35145/jabt.v1i1.22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The number of tourist attractions that are not yet well known, reinforced by the release of Pekanbaru City Government data that the tourism sector only accounts for about 0.9% of the national tourism sector. Therefore, this study aims to optimize the determination of Pekanbaru city tourist travel routes by using genetic algorithms or Genetic Algorithms. Genetic algortima process generally consists of several stages, starting from the initial generation, determination of fitness, crossover stage, mutation to the generation of advanced stages. With an accuracy rate of the best offered solutions reaching around 88% and an average solution search of about 19 seconds per iteration on a constant 100x trial, the results of this study can be used to help general users or Tour & Travel businesses in determining travel routes more optimal travel and a better travel experience.\",\"PeriodicalId\":224855,\"journal\":{\"name\":\"Journal of Applied Business and Technology\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Business and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.35145/jabt.v1i1.22\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Business and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35145/jabt.v1i1.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
APPLICATION OF GENETIC ALGORITHM IN TOURISM ROUTE OPTIMIZATION IN PEKANBARU CITY
The number of tourist attractions that are not yet well known, reinforced by the release of Pekanbaru City Government data that the tourism sector only accounts for about 0.9% of the national tourism sector. Therefore, this study aims to optimize the determination of Pekanbaru city tourist travel routes by using genetic algorithms or Genetic Algorithms. Genetic algortima process generally consists of several stages, starting from the initial generation, determination of fitness, crossover stage, mutation to the generation of advanced stages. With an accuracy rate of the best offered solutions reaching around 88% and an average solution search of about 19 seconds per iteration on a constant 100x trial, the results of this study can be used to help general users or Tour & Travel businesses in determining travel routes more optimal travel and a better travel experience.
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