淡江大學機構典藏:Item 987654321/119509
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62822/95882 (66%)
造访人次 : 4015872      在线人数 : 545
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/119509


    题名: Optimal ordering policies for deteriorating items with a return period and price-dependent demand under two-phase advance sales
    作者: Cheng, Meu-Chuan;Hsieh, Tsu-Pang;Lee, Hsiu-Mei;Ouyang, Liang-Yuh
    关键词: Inventory;Deteriorating;Return period;Price-dependent demand;Two-phase advance sales
    日期: 2020-06
    上传时间: 2020-11-11 12:10:14 (UTC+8)
    摘要: In this article, we establish an inventory model for deteriorating items with a return period and price-dependent demand for the retailer who offers two-phase advance sales to his/her customers. The replenishment cycle is divided into two sales periods: one is the two-phase advance sales period, and the other is the spot sales period. Before customers with reservations receive their orders, they may cancel the order. On the other hand, when the customers receive the order, they can make a request to return products for any reason during the return period. We provide an easy-to-use method to obtain the optimal selling price and the optimal sales period to achieve the retailer’s maximum total profit. Finally, we give numerical examples to illustrate the solution procedure. We perform a sensitivity analysis to investigate the effect of changes of some main parameter values on the optimal solution and provide an economic interpretation.
    關聯: Operational Research 20(2), p.585-604
    DOI: 10.1007/s12351-017-0359-9
    显示于类别:[會計學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML111检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈