Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY International Journal of Production Management and Engineering Pub Date : 2022-01-31 DOI:10.4995/ijpme.2022.16736
H. Al-Khazraji
{"title":"Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem","authors":"H. Al-Khazraji","doi":"10.4995/ijpme.2022.16736","DOIUrl":null,"url":null,"abstract":"Many important problems in engineering management can be formulated as Resource Assignment Problem (RAP). The Workers Assignment Problem (WAP) is considered as a sub-class of RAP which aims to find an optimal assignment of workers to a number of tasks in order to optimize certain objectives. WAP is an NP-hard combinatorial optimization problem. Due to its importance, several algorithms have been developed to solve it. In this paper, it is considered that a manager is required to provide a training course to his workers in order to improve their level of skill or experience to have a sustainable competitive advantage in the industry. The training cost of each worker to perform a particular job is different. The WAP is to find the best assignment of workers to training courses such that the total training cost is minimized. Two metaheuristic optimizations named Whale Optimization Algorithm (WOA) and Flower Pollination Algorithm (FPA) are utilized to final the optimal solution that reduces the total cost. MATLAB Software is used to perform the simulation of the two proposed methods into WAP. The computational results for a set of randomly generated problems of various sizes show that the FPA is able to find good quality solutions.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Production Management and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4995/ijpme.2022.16736","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Many important problems in engineering management can be formulated as Resource Assignment Problem (RAP). The Workers Assignment Problem (WAP) is considered as a sub-class of RAP which aims to find an optimal assignment of workers to a number of tasks in order to optimize certain objectives. WAP is an NP-hard combinatorial optimization problem. Due to its importance, several algorithms have been developed to solve it. In this paper, it is considered that a manager is required to provide a training course to his workers in order to improve their level of skill or experience to have a sustainable competitive advantage in the industry. The training cost of each worker to perform a particular job is different. The WAP is to find the best assignment of workers to training courses such that the total training cost is minimized. Two metaheuristic optimizations named Whale Optimization Algorithm (WOA) and Flower Pollination Algorithm (FPA) are utilized to final the optimal solution that reduces the total cost. MATLAB Software is used to perform the simulation of the two proposed methods into WAP. The computational results for a set of randomly generated problems of various sizes show that the FPA is able to find good quality solutions.
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
鲸鱼优化算法与花授粉算法解决工人分配问题的比较研究
工程管理中的许多重要问题可以归结为资源分配问题。工人分配问题(WAP)被认为是RAP的一个子类,旨在找到工人对多个任务的最优分配,以优化某些目标。WAP是一个NP难的组合优化问题。由于其重要性,已经开发了几种算法来解决它。在本文中,管理者需要为其员工提供培训课程,以提高他们的技能或经验水平,从而在行业中具有可持续的竞争优势。每个工人执行特定工作的培训成本是不同的。WAP旨在为员工找到培训课程的最佳分配,从而将总培训成本降至最低。利用Whale Optimization Algorithm(WOA)和Flower Pollination Algorithms(FPA)两种元启发式优化算法来最终获得降低总成本的最优解。利用MATLAB软件对所提出的两种方法进行WAP仿真。对一组不同大小的随机生成问题的计算结果表明,FPA能够找到高质量的解。
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 去求助
来源期刊
CiteScore
2.10
自引率
13.30%
发文量
18
审稿时长
20 weeks
期刊最新文献
Supply chain risk assessment and mitigation under the global pandemic COVID-19 Heijunka-Levelling customer orders: A systematic literature review Hybrid genetic algorithm to minimize scheduling cost with unequal and job dependent earliness tardiness cost An industry maturity model for implementing Machine Learning operations in manufacturing Principles of cellular manufacturing/engineering/management: case studies and explications
×
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