配置Ira Stationary员工的基因算法

Kurniasari Abram, N. Achmad, Muhammad Rezky Friesta Payu, Nurwan Nurwan, D. Wungguli, Asriadi Asriadi
{"title":"配置Ira Stationary员工的基因算法","authors":"Kurniasari Abram, N. Achmad, Muhammad Rezky Friesta Payu, Nurwan Nurwan, D. Wungguli, Asriadi Asriadi","doi":"10.34312/euler.v11i1.17364","DOIUrl":null,"url":null,"abstract":"Employee scheduling is an activity plan for time sharing that contains a schedule for carrying out planned activities in the form of a table. This study aims to create an employee schedule model using a Genetic Algorithm, which is a heuristic method inspired by the process of natural selection, the strong will survive and reproduce, the stages of the Genetic Algorithm are population initialization, fitness value, selection, crossover, and mutation. The study results show an optimal model consisting of at most two shifts with a maximum of two holidays a week and not consecutively.","PeriodicalId":30843,"journal":{"name":"Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Algoritma Genetika Untuk Penjadwalan Karyawan Ira Stationary\",\"authors\":\"Kurniasari Abram, N. Achmad, Muhammad Rezky Friesta Payu, Nurwan Nurwan, D. Wungguli, Asriadi Asriadi\",\"doi\":\"10.34312/euler.v11i1.17364\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Employee scheduling is an activity plan for time sharing that contains a schedule for carrying out planned activities in the form of a table. This study aims to create an employee schedule model using a Genetic Algorithm, which is a heuristic method inspired by the process of natural selection, the strong will survive and reproduce, the stages of the Genetic Algorithm are population initialization, fitness value, selection, crossover, and mutation. The study results show an optimal model consisting of at most two shifts with a maximum of two holidays a week and not consecutively.\",\"PeriodicalId\":30843,\"journal\":{\"name\":\"Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.34312/euler.v11i1.17364\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34312/euler.v11i1.17364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

员工日程安排是用于时间共享的活动计划,它以表的形式包含执行计划活动的时间表。本研究旨在利用遗传算法建立员工调度模型,遗传算法是一种启发于自然选择过程的启发式方法,强者生存和繁殖,遗传算法的阶段为群体初始化、适应度值、选择、交叉和突变。研究结果表明,最优模型是每周最多两个班次,最多两个假期,并且不连续。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algoritma Genetika Untuk Penjadwalan Karyawan Ira Stationary
Employee scheduling is an activity plan for time sharing that contains a schedule for carrying out planned activities in the form of a table. This study aims to create an employee schedule model using a Genetic Algorithm, which is a heuristic method inspired by the process of natural selection, the strong will survive and reproduce, the stages of the Genetic Algorithm are population initialization, fitness value, selection, crossover, and mutation. The study results show an optimal model consisting of at most two shifts with a maximum of two holidays a week and not consecutively.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
9
审稿时长
16 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信