Extensions from Stochastic Capacity Rationing Decision Approach
碩士 === 國立清華大學 === 工業工程與工程管理學系 === 96 === When the expected demands of a make-to-order manufacturer exceeds its available capacity, a decision procedure, called dynamic stochastic capacity rationing procedure (DSCR), proposed by Hung and Lee (2007) can effectively solve such a stochastic order select...
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ndltd-TW-096NTHU50310962015-11-27T04:04:17Z http://ndltd.ncl.edu.tw/handle/50619851336406828057 Extensions from Stochastic Capacity Rationing Decision Approach 隨機產能配給決策方法之延伸 Ping-Heng Tsai 蔡秉亨 碩士 國立清華大學 工業工程與工程管理學系 96 When the expected demands of a make-to-order manufacturer exceeds its available capacity, a decision procedure, called dynamic stochastic capacity rationing procedure (DSCR), proposed by Hung and Lee (2007) can effectively solve such a stochastic order selection problem. Unlike previous studies, their approach does not need to classify product by profit; furthermore, the profit and capacity requirement of a random order are assumed as continuous random numbers. This study makes three extensions from original approach by Hung and Lee (2007) in order to make the decision procedure more applicable in actual practices. (1) In Hung and Lee’s original problems, there is no standard product; i.e., classification is impossible. In the first extension of this study, we assume the products can be classified into a discrete number profit classes. Under such an assumption, various approaches proposed previously are applicable and, in this study, are used to compare with the modified DSCR. (2) In many manufacturing firms, the inquiry issued by a customer includes the request quantity and request delivery date. Then, a sale person of the manufacturing firm replies with a quotation that includes an asking price and a confirmed delivery date. Under such a business process scenario, the price (or, profit) is not a given parameter to the decision maker. Instead, the decision maker should determine the price (or, profit). The second extension of this study provides an aiding tool for the decision maker to determine the quotation prices of the customer inquiry. (3) Some manufacturing business allow partial order fulfillment. Under such a condition, how we determine the quantity of the fulfilled partial order in order to maximize the expected profit is the focus of the third extension. Yi-Feng Hung 洪一峯 2008 學位論文 ; thesis 36 en_US |
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碩士 === 國立清華大學 === 工業工程與工程管理學系 === 96 === When the expected demands of a make-to-order manufacturer exceeds its available capacity, a decision procedure, called dynamic stochastic capacity rationing procedure (DSCR), proposed by Hung and Lee (2007) can effectively solve such a stochastic order selection problem. Unlike previous studies, their approach does not need to classify product by profit; furthermore, the profit and capacity requirement of a random order are assumed as continuous random numbers. This study makes three extensions from original approach by Hung and Lee (2007) in order to make the decision procedure more applicable in actual practices.
(1) In Hung and Lee’s original problems, there is no standard product; i.e., classification is impossible. In the first extension of this study, we assume the products can be classified into a discrete number profit classes. Under such an assumption, various approaches proposed previously are applicable and, in this study, are used to compare with the modified DSCR.
(2) In many manufacturing firms, the inquiry issued by a customer includes the request quantity and request delivery date. Then, a sale person of the manufacturing firm replies with a quotation that includes an asking price and a confirmed delivery date. Under such a business process scenario, the price (or, profit) is not a given parameter to the decision maker. Instead, the decision maker should determine the price (or, profit). The second extension of this study provides an aiding tool for the decision maker to determine the quotation prices of the customer inquiry.
(3) Some manufacturing business allow partial order fulfillment. Under such a condition, how we determine the quantity of the fulfilled partial order in order to maximize the expected profit is the focus of the third extension.
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Yi-Feng Hung |
author_facet |
Yi-Feng Hung Ping-Heng Tsai 蔡秉亨 |
author |
Ping-Heng Tsai 蔡秉亨 |
spellingShingle |
Ping-Heng Tsai 蔡秉亨 Extensions from Stochastic Capacity Rationing Decision Approach |
author_sort |
Ping-Heng Tsai |
title |
Extensions from Stochastic Capacity Rationing Decision Approach |
title_short |
Extensions from Stochastic Capacity Rationing Decision Approach |
title_full |
Extensions from Stochastic Capacity Rationing Decision Approach |
title_fullStr |
Extensions from Stochastic Capacity Rationing Decision Approach |
title_full_unstemmed |
Extensions from Stochastic Capacity Rationing Decision Approach |
title_sort |
extensions from stochastic capacity rationing decision approach |
publishDate |
2008 |
url |
http://ndltd.ncl.edu.tw/handle/50619851336406828057 |
work_keys_str_mv |
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