Camilo de Lellis Barreto Junior, Alexandre Cardoso, E. Lamounier, K. Yamanaka
{"title":"Genetic Algorithm-Based Strategy for Routing in Virtual Electrical Substations Aiming for Security","authors":"Camilo de Lellis Barreto Junior, Alexandre Cardoso, E. Lamounier, K. Yamanaka","doi":"10.1109/CLEI.2018.00032","DOIUrl":null,"url":null,"abstract":"Maintenance in electrical substation equipment involves several daily risks to the worker. When carrying out the maintenance of a large equipment, a truck is assigned to the task. It is not any place that the truck has the ability to travel, nor the workers have the free transition through the place. The objective of this work is to develop a Genetic Algorithm to solve the problem, to create a route where the level of danger is low and does not pose a risk to the health of the worker. To test the genetic algorithm, a substation virtual environment was used where the dimensions and distances are reliable for a real environment. In order to do so, the map division strategy and the creation of individuals with variable sizes were applied. The results were satisfactory, obtaining a route from the point of departure and the point of arrival.","PeriodicalId":379986,"journal":{"name":"2018 XLIV Latin American Computer Conference (CLEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 XLIV Latin American Computer Conference (CLEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLEI.2018.00032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Maintenance in electrical substation equipment involves several daily risks to the worker. When carrying out the maintenance of a large equipment, a truck is assigned to the task. It is not any place that the truck has the ability to travel, nor the workers have the free transition through the place. The objective of this work is to develop a Genetic Algorithm to solve the problem, to create a route where the level of danger is low and does not pose a risk to the health of the worker. To test the genetic algorithm, a substation virtual environment was used where the dimensions and distances are reliable for a real environment. In order to do so, the map division strategy and the creation of individuals with variable sizes were applied. The results were satisfactory, obtaining a route from the point of departure and the point of arrival.