考虑检验误差和检验改进投资的经济订货量模型的最优订购策略

Q3 Engineering
L. Ouyang, Chia-Hsien Su, Chia-Huei Ho, Chih-te Yang
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引用次数: 2

摘要

消费者权益的提升已促使企业越来越关注产品质量。企业无法在销售前识别出有缺陷的产品,导致退货成本增加,销售收入减少,声誉受损,竞争力下降。本文研究了零售商在收到的产品中发现次品的经济订货量模型。虽然零售商进行质量检查,但检查过程并不完善。我们假设在产品质量检验过程中出现第一类和第二类检验错误,并且市场需求率对第二类检验错误敏感。为了改进检验,零售商投入资金来减少第二类检验错误。本研究探讨了最优订货量和测试对单位时间内总利润最大化的作用。通过数学分析证明了最优解的存在性。然后开发了一种算法来计算最优解。最后通过数值算例说明了求解过程,并对主要参数进行了敏感性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Ordering Policy for an Economic Order Quantity Model with Inspection Errors and Inspection Improvement Investment
The rise of consumer rights has caused businesses to focus increasingly on product quality. The inability of businesses to identify defective items before selling them results in higher return costs, decreased sales revenue, damaged reputations, and decreased competitiveness. This study examines the economic order quantity (EOQ) model in which the retailer discovers defective goods among received products. Although retailers conduct quality inspections, the inspection process is imperfect. We assume that Type I and Type II inspection errors occur during product quality inspection and that the market demand rate is sensitive to Type II inspection errors. To improve inspection, the retailer invests capital to decrease Type II inspection errors. This study investigates the optimal order quantity and the power of the test to maximize total profit per unit time. Mathematical analysis is used to show the optimal solution exists. An algorithm is then developed to calculate the optimal solution. Finally, numerical examples demonstrate the solution process and sensitivity analysis with respect to major parameters is carried out.
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来源期刊
International Journal of Information and Management Sciences
International Journal of Information and Management Sciences Engineering-Industrial and Manufacturing Engineering
CiteScore
0.90
自引率
0.00%
发文量
0
期刊介绍: - Information Management - Management Sciences - Operation Research - Decision Theory - System Theory - Statistics - Business Administration - Finance - Numerical computations - Statistical simulations - Decision support system - Expert system - Knowledge-based systems - Artificial intelligence
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