淡江大學機構典藏:Item 987654321/34140
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 64191/96979 (66%)
造访人次 : 8443761      在线人数 : 8096
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/987654321/34140


    题名: 以滾動週期可允諾存量為基礎之訂單競標決策 : 模糊方法與遺傳演算法之應用
    其它题名: Bidding decision based on a rolling horizon available-to-promise mechanism : solution by fuzzy approach and genetic algorithm
    作者: 吳孟聰;Wu, Meng-tsung
    贡献者: 淡江大學資訊管理學系碩士班
    鄭啟斌;Cheng, Chi-bin
    关键词: 逆向拍賣;競標;進階可允諾量;模糊理論;遺傳演算法;Reverse Auction;Bidding;Advanced Available-to-Promise;Fuzzy Set Theory;Genetic Algorithm
    日期: 2009
    上传时间: 2010-01-11 04:57:51 (UTC+8)
    摘要: 本研究之目的在以競標方式爭取訂單的供應鏈環境中，提供賣方(供應商)決定其競標價格的決策機制。為了提升供應商之利潤與得標機會，本研究整合競標決策、訂單允諾機制與生產計劃，以交期允諾及生產成本做為競標價格決策之基礎。其中，訂單允諾機制乃以進階可允諾量(Advanced Available-to-Promise, AATP)之觀念為基礎，亦即考慮未來可應用產能之最佳配置。本研究以混合整數規劃(Mixed Integer Programming, MIP)模型來描述競標決策問題，模型中並包含模糊限制式以表達決策者在制定標價時對顧客價格容忍度的認知。在本研究之規劃環境中，訂單的允諾乃採批次處理與滾動規劃週期的設計，亦即每隔一固定期間，供應商會重新審視所收到而未允諾或已允諾但尚未完成生產之訂單，並重新執行上述之決策模式以更新生產計畫。模型之求解過程包含以模糊方法搜尋最大利潤與最大得標機會之妥協解，並以遺傳演算法(Genetic Algorithm, GA)實作求解程序。本研究以電腦模擬的方式進行實驗以驗證本研究方法之績效。
    This study integrates the bidding decision and production planning based on the concept of advanced available-to-promise (AATP) inventory with a rolling planning horizon. Customer requests arrive in a random fashion, and bidding decisions are made for a batch of requests collected over a batching interval. This decision process repeated for every specified batching interval, and the current decision-making must take into account the previously committed orders in earlier phases. The problem is formulated as a mixed integer programming model with fuzzy constraints, which express the decision-maker’s subjective judgment regarding customer’s price tolerance. The proposed model embeds the AATP concept to support accurate computation of profit and customer order promising. A genetic algorithm is developed to solve the problem. Performance of the proposed approach is evaluated through experiments conducted by computer simulation.
    显示于类别:[資訊管理學系暨研究所] 學位論文

    文件中的档案:

    档案 大小格式浏览次数
    0KbUnknown423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