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|Title:||RETRACTED ARTICLE: Determination and analysis of inventory policies for timevarying demand problem applied on continuous probability distributed demand||Authors:||Kanchanasuntorn, K.
|Keywords:||Determination and analysis;Discrete demand;Inventory policies||Issue Date:||2010||Publisher:||University of the Thai Chamber of Commerce||Source:||K. Kanchanasuntorn, M. Neawdong, S. Yodsuwa (2010) RETRACTED ARTICLE: Determination and analysis of inventory policies for timevarying demand problem applied on continuous probability distributed demand., 443-448.||Conference:||ICEMT 2010 2010 International Conference on Education and Management Technology||Abstract:||According to one of the most interested of inventory management issue in industrial and logistics management in today competitive environment, the aim of this work is to develop a determination tools for inventory parameters calculation and analyze the applicable of those parameters into various probability distributed demand. The calculation program incorporated in Microsoft Excel are developed and a series of simulation experiments are also conducted using the developed program in orderto compare the total inventory relevant cost of these policies The studies are conducted for different cases of inventory problem with 3different probability distributions of demand and the obtained results are analyzed and concluded. The program are developed for comparing 8 inventory policies for discrete demand pattern comprising of Adaptation EOQ, LotForLot,Periodic Order Quantity, WagnerWhitin, SilverMealAlgorithm, Least Unit Cost, PartPeriod, and Incumented PartPeriod. Visual Basic Application (VBA) code, a part of Microsoft Excel, is constructed in order to receive input data, to calculate the inventory policies and relevant total cost and to display program outputs. After verified and validated, the program is implemented for determining inventory policies of various scenarios of problems, including uniform, normally, and discrete distributed demand pattern. The analysis results obtained from program can be concluded that the WagnerWhitinAlgorithm is the best way to provide the lowest total cost by determining the order quantity in all appropriate periods. However, when demand in the first period is equal to 0, we found that the Silver Meal Algorithm may provide the better results than those of WagnerWhitin. So, in those cases, total relevant cost of the two policies should be compared.||URI:||https://scholar.utcc.ac.th/handle/6626976254/3613||Rights:||This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.|
|Appears in Collections:||RSO: Conference Papers|
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