Performance Analysis in Multi-KPI Optimizations

Gökhan Koç
{"title":"Performance Analysis in Multi-KPI Optimizations","authors":"Gökhan Koç","doi":"10.18100/ijamec.796351","DOIUrl":null,"url":null,"abstract":"Importance of resource planning at airports, ports, logistic centers and similar operation points is increasing significantly each day due to competitions, intensities and irregularities in operations. Multi-objective optimization algorithms try to reach the user defined objectives of the related operations as much as possible but the performance of these algorithms starts to differ while the number of defined Key Performance Indicators (KPI’s) are increasing. In multi-KPI optimization algorithms, there are many issues and parameters to consider which affect the optimizer performances such as; relationship between KPI’s, the number of KPI’s, number of resources, tasks. In addition, due to some specific business rules in the operation, not every resource can be assigned to every task and the optimization algorithm needs to consider these rules when generating allocation plan. Within the scope of this study, an optimization algorithm which is developed by TAV Technologies is used to analysis optimizer performance changes according to the number of defined KPI’s. For the same resource and task group, the optimization algorithm configured with different KPI combinations and run repeatedly. Except for the KPI definitions, all other optimizer inputs were kept constant in all tests and the results were compared with each other. Specific business rules were ignored in this study to analysis test results clearly.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied Mathematics Electronics and Computers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18100/ijamec.796351","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

Importance of resource planning at airports, ports, logistic centers and similar operation points is increasing significantly each day due to competitions, intensities and irregularities in operations. Multi-objective optimization algorithms try to reach the user defined objectives of the related operations as much as possible but the performance of these algorithms starts to differ while the number of defined Key Performance Indicators (KPI’s) are increasing. In multi-KPI optimization algorithms, there are many issues and parameters to consider which affect the optimizer performances such as; relationship between KPI’s, the number of KPI’s, number of resources, tasks. In addition, due to some specific business rules in the operation, not every resource can be assigned to every task and the optimization algorithm needs to consider these rules when generating allocation plan. Within the scope of this study, an optimization algorithm which is developed by TAV Technologies is used to analysis optimizer performance changes according to the number of defined KPI’s. For the same resource and task group, the optimization algorithm configured with different KPI combinations and run repeatedly. Except for the KPI definitions, all other optimizer inputs were kept constant in all tests and the results were compared with each other. Specific business rules were ignored in this study to analysis test results clearly.
多kpi优化中的性能分析
在机场、港口、物流中心和类似的作业点,由于作业的竞争、强度和不规范,资源规划的重要性日益显著。多目标优化算法试图尽可能地达到用户定义的相关操作目标,但随着定义的关键绩效指标(KPI)的增加,这些算法的性能开始出现差异。在多kpi优化算法中,有许多影响优化器性能的问题和参数需要考虑,如;KPI之间的关系,KPI的数量,资源数量,任务。此外,由于操作中存在一些特定的业务规则,并不是每个资源都可以分配给每个任务,优化算法在生成分配计划时需要考虑这些规则。在本研究范围内,使用TAV Technologies开发的优化算法,根据定义的KPI数量分析优化器的性能变化。对于同一资源和任务组,优化算法配置不同的KPI组合并重复运行。除了KPI定义之外,所有其他优化器输入在所有测试中都保持不变,并相互比较结果。为了清楚地分析测试结果,本研究忽略了具体的业务规则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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