劳动力规划的蚁群优化算法:蒸发参数的影响

S. Fidanova, Gabriel Luque, O. Roeva, M. Ganzha
{"title":"劳动力规划的蚁群优化算法:蒸发参数的影响","authors":"S. Fidanova, Gabriel Luque, O. Roeva, M. Ganzha","doi":"10.15439/2019F300","DOIUrl":null,"url":null,"abstract":"Optimization of the production process is important for every factory or organization. The better organization can be done by optimization of the workforce planing. The main goal is decreasing the assignment cost of the workers with the help of which, the work will be done. The problem is NP-hard, therefore it can be solved with algorithms coming from artificial intelligence. The problem is to select employers and to assign them to the jobs to be performed. The constraints of this problem are very strong and for the algorithms is difficult to find feasible solutions. We apply Ant Colony Optimization Algorithm to solve the problem.We investigate the algorithm performance according evaporation parameter. The aim is to find the best parameter setting.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ant Colony optimization Algorithm for Workforce Planning: Influence of the Evaporation Parameter\",\"authors\":\"S. Fidanova, Gabriel Luque, O. Roeva, M. Ganzha\",\"doi\":\"10.15439/2019F300\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimization of the production process is important for every factory or organization. The better organization can be done by optimization of the workforce planing. The main goal is decreasing the assignment cost of the workers with the help of which, the work will be done. The problem is NP-hard, therefore it can be solved with algorithms coming from artificial intelligence. The problem is to select employers and to assign them to the jobs to be performed. The constraints of this problem are very strong and for the algorithms is difficult to find feasible solutions. We apply Ant Colony Optimization Algorithm to solve the problem.We investigate the algorithm performance according evaporation parameter. The aim is to find the best parameter setting.\",\"PeriodicalId\":168208,\"journal\":{\"name\":\"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15439/2019F300\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15439/2019F300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

生产过程的优化对每个工厂或组织都很重要。通过对劳动力规划的优化,可以实现更好的组织。主要目标是降低工人的分配成本,在此帮助下,工作将完成。这个问题是np困难的,因此可以用来自人工智能的算法来解决。问题是选择雇主并将他们分配到要执行的工作。该问题的约束条件很强,算法很难找到可行的解。我们采用蚁群优化算法来解决这个问题。根据蒸发参数考察了算法的性能。目的是找到最佳的参数设置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Ant Colony optimization Algorithm for Workforce Planning: Influence of the Evaporation Parameter
Optimization of the production process is important for every factory or organization. The better organization can be done by optimization of the workforce planing. The main goal is decreasing the assignment cost of the workers with the help of which, the work will be done. The problem is NP-hard, therefore it can be solved with algorithms coming from artificial intelligence. The problem is to select employers and to assign them to the jobs to be performed. The constraints of this problem are very strong and for the algorithms is difficult to find feasible solutions. We apply Ant Colony Optimization Algorithm to solve the problem.We investigate the algorithm performance according evaporation parameter. The aim is to find the best parameter setting.
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
0
期刊最新文献
Efficient Support Vector Regression with Reduced Training Data A Deep Learning and Multimodal Ambient Sensing Framework for Human Activity Recognition Predicting Blood Glucose using an LSTM Neural Network License Plate Detection with Machine Learning Without Using Number Recognition Tool-assisted Surrogate Selection for Simulation Models in Energy Systems
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1