博碩士論文 91426017 完整後設資料紀錄

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DC.contributor工業管理研究所zh_TW
DC.creator張瑜紋zh_TW
DC.creatorYu-Wen Changen_US
dc.date.accessioned2004-6-22T07:39:07Z
dc.date.available2004-6-22T07:39:07Z
dc.date.issued2004
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=91426017
dc.contributor.department工業管理研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract本研究旨在探討單一製造商與單一零售商的通路結構下,探討有限規劃週期內,產品具有指數損耗特性之聯合訂購與定價決策。首先,我們考量到價格對於需求的影響,因此,將需求假設成與價格相關的函數,以線性模組的方式納入模式中思考,並在採購成本會隨著時間和數量變化的機制下,建構以零售商利潤極大化的角度出發之利潤函數,且分析零售商之利潤函數是否會因為銷售價格因子的考量以及不同的採購時點與不同的採購數量而有所改變,進而釐定定價與訂購週期之聯合決策的問題。 全文在固定的計畫水平期間內考量,同時針對三種情況討論相關的聯合定價與訂購週期決策,分別是允許缺貨、不允許缺貨且完全缺貨待補,和不允許缺貨且部分缺貨待。其中最後者的比例為一和時間相關的函數。在以上提及的三種範疇下,分別先證明其利潤函數具有凹函數特性,更根據這些特性,提供一套求解程序,以決定最適的產品銷售售價、最適存貨補充週期和訂購數量,訂定最佳的存貨補充策略。zh_TW
dc.description.abstractThe objective of this study is to develop a deterministic inventory model where demand decreases linearly with price, planning horizon is assumed to be finite and the replenishment cycles are constant.Unlike traditional inventory models that seek to minimize cost, the objective of this study is to maximize profit. The net profit maximizing ordering policy and price are determined when purchase cost is time and quantity-dependent. We consider the cases that do not allow shortages and the ones that allow shortages. The shortages are completely backlogging and partial backlogging which ensures that the rate of backlogged demand increases as the waiting time to the following replenishment point decreases.en_US
DC.subject損耗性商品zh_TW
DC.subject兩階段定價zh_TW
DC.subject部分缺貨待補zh_TW
DC.subject完全缺貨待補zh_TW
DC.subjecttwo-part tariffen_US
DC.subjectpartial backloggingen_US
DC.subjectcompletely backloggingen_US
DC.subjectdeteriorating itemen_US
DC.title購買成本與時間和數量相依下損耗性產品的最佳定價和補貨週期zh_TW
dc.language.isozh-TWzh-TW
DC.titleOptimal pricing and replenishment cycle for a deteriorating item when purchase cost is time and quantity-dependenten_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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