English  |  正體中文  |  简体中文  |  Items with full text/Total items : 57505/91036 (63%)
Visitors : 13425746      Online Users : 284
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/19852

    Title: A minimax distribution free procedure for mixed inventory model involving variable lead time with fuzzy demand
    Authors: 歐陽良裕;Ouyang, Liang-yuh;Yao, Jing-shing
    Contributors: 淡江大學經營決策學系
    Keywords: Inventory;Membership function;Extension principle;Fuzzy total cost;Minimax distribution free procedure
    Date: 2002-04
    Issue Date: 2009-11-30 12:24:27 (UTC+8)
    Publisher: Elsevier
    Abstract: In a recent paper, Ouyang and Wu applied the minimax decision approach to solve a continuous review mixed inventory model in which the lead time demand distribution information is unknown but the annual demand is fixed and given. However, in the practical situation, the annual demand probably incurs disturbance due to various uncertainties. In this article, we attempt to modify Ouyang and Wu's model by considering two fuzziness of annual demand (i.e., fuzzy number of annual demand and statistic-fuzzy number of annual demand) and to investigate a computing schema for the continuous review inventory model in the fuzzy sense. We give an algorithm procedure to obtain the optimal ordering strategy for each case.
    Relation: Computers & Operations Research 29(5), pp.471-487
    DOI: 10.1016/S0305-0548(00)00085-X
    Appears in Collections:[管理科學學系暨研究所] 期刊論文

    Files in This Item:

    File SizeFormat

    All items in 機構典藏 are protected by copyright, with all rights reserved.

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