Using system simulation to search for the optimal multi-ordering policy for perishable goods

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY International Journal of Production Management and Engineering Pub Date : 2019-01-31 DOI:10.4995/IJPME.2019.10745
Yun Huang, X. Chang, Yan Ding
{"title":"Using system simulation to search for the optimal multi-ordering policy for perishable goods","authors":"Yun Huang, X. Chang, Yan Ding","doi":"10.4995/IJPME.2019.10745","DOIUrl":null,"url":null,"abstract":"This paper explores the possibility that perishable goods can be ordered several times in a single period after considering the cost of Marginal contribution, Marginal loss, Shortage, and Purchasing under stochastic demand. In order to determine the optimal ordering quantity to improve the traditional newsvendor and maximize the total expected profits, and then sensitivity analysis is taken to realize the influence of the parameters on total expected profits and decision variables respectively. In addition, this paper designed a multi-order computerized system with Monte Carlo method to solve the optimal solution under stochastic demand. Based on numerical examples, this paper verified the feasibility and efficiency of the proposed model. Finally, several specific conclusions are drawn for practical applications and future studies.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2019-01-31","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.2019.10745","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

This paper explores the possibility that perishable goods can be ordered several times in a single period after considering the cost of Marginal contribution, Marginal loss, Shortage, and Purchasing under stochastic demand. In order to determine the optimal ordering quantity to improve the traditional newsvendor and maximize the total expected profits, and then sensitivity analysis is taken to realize the influence of the parameters on total expected profits and decision variables respectively. In addition, this paper designed a multi-order computerized system with Monte Carlo method to solve the optimal solution under stochastic demand. Based on numerical examples, this paper verified the feasibility and efficiency of the proposed model. Finally, several specific conclusions are drawn for practical applications and future studies.
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
利用系统仿真的方法,寻找易腐货物的最优多重订货策略
本文在考虑了随机需求下的边际贡献、边际损失、短缺和采购成本后,探讨了易腐货物在一个时期内可以多次订购的可能性。为了确定改进传统报刊供应商的最优订购量,使总期望利润最大化,然后进行敏感性分析,分别认识到参数对总期望利润和决策变量的影响。此外,本文还用蒙特卡罗方法设计了一个多阶计算机系统来求解随机需求下的最优解。通过算例验证了该模型的可行性和有效性。最后,得出了一些具体的结论,以供实际应用和未来的研究。
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