{"title":"Symbiotic organisms search algorithm for scheduling laboratory sessions in University","authors":"C. Pickerling, Hendrawan Armanto, E. Setyaningsih","doi":"10.1109/CAIPT.2017.8320698","DOIUrl":null,"url":null,"abstract":"Numerous research has been done on scheduling, however only a few results an optimal schedule. Thus are schedule is made manually. The most frequently used algorithm for scheduling problem is genetic algorithm, but in this research we used Symbiotic Organisms Search Algorithm. This algorithm is used to simulate the behavior of organisms in their environment because of their dependence on the survival of the other species. We tested the algorithm for scheduling laboratory activities and after a number of trials, we concluded that this algorithm is able to provide an optimal solution for scheduling problem with 87.17% accuracy.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAIPT.2017.8320698","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
Numerous research has been done on scheduling, however only a few results an optimal schedule. Thus are schedule is made manually. The most frequently used algorithm for scheduling problem is genetic algorithm, but in this research we used Symbiotic Organisms Search Algorithm. This algorithm is used to simulate the behavior of organisms in their environment because of their dependence on the survival of the other species. We tested the algorithm for scheduling laboratory activities and after a number of trials, we concluded that this algorithm is able to provide an optimal solution for scheduling problem with 87.17% accuracy.