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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳靜枝(Ching-Chin Chern) | |
| dc.contributor.author | Jui-Chun Chang | en |
| dc.contributor.author | 張睿君 | zh_TW |
| dc.date.accessioned | 2021-06-16T06:30:35Z | - |
| dc.date.available | 2020-08-20 | |
| dc.date.copyright | 2020-08-20 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-07-29 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56873 | - |
| dc.description.abstract | 在高度競爭的市場環境中，許多企業採用多供應商策略以滿足需求與特定合約內容。由於供應商之供應能力通常不盡相同，且所供應的產品之間也具有差異，因此對於在供應鏈網路中間的製造商與分銷商而言，同時控制不同供應來源並滿足多種需求尤為困難。 為了落實多元供應策略，製造商與分銷商不僅需要決定向不同供應商採購的購買量，也必須思考如何將供給分配至不同需求，使得所有需求皆能被成功滿足。然而目前市面上大部分的規劃工具皆以最小化製造成本為唯一目標，所產出的排程規劃雖然成本較低但難以實際執行。為此本研究提出考量多元供應與需求公平性之主規劃排程演算法，期望解決企業在採購規劃上的難題。 本研究所提出的考量多元供應與需求公平性之主規劃排程滿足使用者所訂定的採購方式，並將公平性量化為指標，使用啟發式演算法的方式實作並以整數規劃求解的方式驗證。實際應用層面已使用臺灣一家專業代工生產公司進行情境設計及實測，就規模而言，已將整數規劃求解一小時內無法找到任何可行解的案例壓縮在0.6秒內完成；就結果而言，在滿足指定採購策略的情況下，啟發式演算法規劃結果之總成本與整數規劃求解所能求得的最小總成本的差距平均為4%。 整體而言，本研究提出之演算法可提供重視供給分配公平性且有多元供應需求之製造商與分銷商，迅速且有效地產出公平的多供應商採購規劃排程。 | zh_TW |
| dc.description.abstract | In the highly competitive market environment, most companies adopt the multi-sourcing strategy to satisfy demands and meet specific contract responsibilities. For manufacturers or distributors, whose roles are in the middle of supply chain network, controlling multiple sources of supply and various demands of customers is difficult since suppliers usually have different production capacities and provide products with some discrepancy. To actually implement the multi-sourcing strategy, the manufacturers or distributors have to not only determine purchasing quantities of different vendors, but also think over how to match supplies with demands so that orders are able to be satisfied successfully. Almost all planning tools have the only target of minimizing costs. The planning results are usually inapplicable to fulfill actual requirements in spite of cost minimization. This study proposes a multi-sourcing master planning algorithm to solve the difficulty in generating fair sourcing master plans. The multi-sourcing fairness master planning algorithm (MSFMPA) is proposed to produce a multi-sourcing master plan that satisfies the requirements of sourcing from different vendors and allocating supplies fairly. In terms of scale, MSFMPA can produce a multi-sourcing plan within 0.6 seconds that the MINLP model cannot find any feasible solution within an hour for an identical case. As for quality, MSFMPA successfully fulfills the specific sourcing requirements and the average difference of overall costs is 4%, compared with the results obtained by the MINLP model. The result of this study can help the firms that put emphasis on fairness of a multi-sourcing plan. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T06:30:35Z (GMT). No. of bitstreams: 1 U0001-2307202016190300.pdf: 5229046 bytes, checksum: 20b82ddc36ab2eebe0a3be83323e03fe (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | 論文口試委員審定書 i 謝辭 ii 論文摘要 iii THESIS ABSTRACT iv Contents v List of Tables ix List of Figures xii Chapter 1 Introduction 1 1.1 Background and Motivation 1 1.2 Research Objectives 5 1.3 Research Scope and Limitation 7 Chapter 2 Literature Review 9 2.1 Multiple Sourcing Strategies and Planning 9 2.2 Definition and Development of Fairness 11 2.3 Methods to Solve Master Planning Problems 14 Chapter 3 Problem Description 18 3.1 Problem Description 18 3.2 Assumptions 21 3.3 Parameters and Variables 22 3.4 Objective Functions and Constraints 26 3.5 Summary 31 Chapter 4 Heuristic Multi-Sourcing Fairness Master Planning Algorithm (MSFMPA) 33 4.1 Preliminary Work 35 4.1.1 Compute Priority Weight or Quota Weight 35 4.1.2 Determine Time Weight 38 4.1.3 Construct Initial Deserved Quantity Table 40 4.2 Maximum Allocation Quantity Determination 44 4.3 Supplementary Measures of MSFMPA 46 4.3.1 Case of Supply Supplement 47 4.3.2 Case of Supply Shortage 49 4.4 Fair Supply Allocation 50 4.5 Overall Performance Calculation 51 4.6 Conclusion 52 Chapter 5 Analysis of Algorithm and Model 55 5.1 Prototype Illustration 55 5.2 Scenario Design 59 5.3 Computational Analysis 63 5.3.1 Influences of Factors 63 5.3.2 Comparing indices of MSFMPA with MINLP model 68 5.3.3 Comparing costs of MSFMPA with MINLP model 70 5.4 Testing on a Real-World Case 73 5.4.1 Testing on Automotive Product Line 74 5.4.2 Testing on Industrial Application Product Line 75 5.4.3 Testing on Aviation Product Line 76 5.4.4 Comparisons of Results between Different Product Lines 77 5.5 Conclusion on Analysis of Solutions 80 Chapter 6 Conclusion and Future Work 82 6.1 Conclusion 82 6.2 Future Work 84 Reference 86 Appendix A The Detailed planning results of product line A 91 Appendix B The Detailed planning results of product line B 99 Appendix C The Detailed planning results of product line C 117 | |
| dc.language.iso | en | |
| dc.title | 考量多元供應與需求公平性之主規劃排程演算法 | zh_TW |
| dc.title | A Heuristic Master Planning Algorithm for Multiple Sourcing and Demand Considering Fairness | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蔣明晃(Ming-Huang Chiang),黃奎隆(Kwei-Long Huang),孔令傑(Ling-Chieh Kung) | |
| dc.subject.keyword | 供應鏈,多元供應商,採購分配,排程公平性,主規劃排程, | zh_TW |
| dc.subject.keyword | Supply Chain,Multi-Sourcing,Multiple Supplier,Procurement Allocation,Master Plan Fairness,Master Plan, | en |
| dc.relation.page | 122 | |
| dc.identifier.doi | 10.6342/NTU202001787 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2020-07-30 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
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