利用系统仿真的方法,寻找易腐货物的最优多重订货策略

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
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引用次数: 0

摘要

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