請用此 Handle URI 來引用此文件：
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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 孔令傑(Ling-Chieh Kung) | |
| dc.contributor.author | Wen-Yu Kung | en |
| dc.contributor.author | 龔汶佑 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:11:09Z | - |
| dc.date.available | 2021-11-03 | |
| dc.date.available | 2022-11-24T03:11:09Z | - |
| dc.date.copyright | 2021-11-03 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-10-22 | |
| dc.identifier.citation | Archetti, C., E. Fern´andez, D. L. Huerta-Mu˜noz. 2017. The flexible periodic vehicle routing problem. Computers Operations Research 85 58–70. Archetti, C., E. Fern´andez, D. L. Huerta-Mu˜noz. 2018. A two-phase solution algorithm for the flexible periodic vehicle routing problem. Computers Operations Research 99 27–37. Dong, H., Y. Takada, Wei W., M. Yagiura. 2020. A heuristic algorithm for the periodic vehicle routing problem with flexible delivery dates. Journal of Advanced Mechanical Design, Systems, and Manufacturing 14(5) 1–12. Feillet, D., P. Dejax, M. Gendreau. 2005. Traveling salesman problems with profits. Transportation Science 39(2) 188–205. Hiassat, A., A. Diabat, I. Rahwan. 2017. A genetic algorithm approach for locationinventory-routing problem with perishable products. Journal of Manufacturing Systems 42 93–103. L., Yanhui, Hao G., Lin W., Jing F. 2013. A hybrid genetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under e-supply chain environment. The Scientific World Journal 2013 1–10. Parsamanesh, A. H., E. Roghanian. 2018. Reducing the risk of robbery in flexible periodic vehicle routing problem. 4th International Conference on Industrial and Systems Engineering . Q., Shujin, Shixin L., Qi Z. 2017. The traveling salesman problem with profits considering time-dependent cost and multi-trip mode. 36th Chinese Control Conference (CCC). IEEE, 2899–2903. Veenstra, M., K. J. Roodbergen, L. C. Coelho, S. X. Zhu. 2018. A simultaneous facility location and vehicle routing problem arising in health care logistics in the netherlands. European Journal of Operational Research 268(2) 703–715. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80627 | - |
| dc.description.abstract | 在這篇研究之中，我們考慮了一個提供硬體販售、維修以及保養服務的公司會面臨到的問題。這一個問題包含了設施選址、員工雇用、服務班表規劃以及員工服務路徑規劃。在這個問題之中，顧客的需求是週期性的，需要在一定期間之內被服務到一定次數。顧客需求的服務次數不一定要完全被滿足，然而，不被滿足時公司必須支付顧客額外賠償。服務班表的規劃也有嚴格的日期限制。由於這個問題十分複雜，雖然我們能建構一個混合整數規劃模型來描述這個問題，但這個模型卻會因規模過於龐大而無法被求解。為了解決這個問題，我們將問題拆成雙層模型以方便演算法的開發。我們提出了一個由基因演算法以及貪婪演算法所結合的演算法去分別求解這個雙層模型。經過數值實驗與案例分析，我們驗證了我們提出之演算法能在合理時間內得到接近最佳解的可行解。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:11:09Z (GMT). No. of bitstreams: 1 U0001-2110202115305000.pdf: 2191963 bytes, checksum: ee6e608058e5fd0182f535ac8dc73730 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | "Verification letter ii Chinese Abstract iii English Abstract iv List of Figures vii List of Tables ix 1 Introduction 1 1.1 Background and motivation . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Research objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Research plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Literature Review 5 2.1 Facility location problem combined with vehicle routing problem . . . . . 5 2.2 Traveling salesman problem with customer selection . . . . . . . . . . . . 8 2.3 Vehicle routing problem with periodic demand . . . . . . . . . . . . . . . 9 3 Problem Description and Formulation 12 3.1 Model description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.2 Integrated model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.3 Sets, parameters, and variables for the integrated model . . . . . . . . . . 16 4 Algorithms 19 4.1 Decomposition into a bi-level model . . . . . . . . . . . . . . . . . . . . . 19 4.1.1 Model formuation . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.1.2 Worker factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.1.3 Bi-level model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.1.4 Bi-level algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.2 HH algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.2.1 Genetic algorithm for facility location selection . . . . . . . . . . 23 4.2.2 Greedy algorithm for scheduling . . . . . . . . . . . . . . . . . . . 24 5 Numerical study 27 5.1 Setting of experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.1.1 Fixed parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.1.2 Random parameters . . . . . . . . . . . . . . . . . . . . . . . . . 29 5.1.3 Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 5.1.4 Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 5.1.5 Benchmark model . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 5.1.6 Settings of heuristic algorithm . . . . . . . . . . . . . . . . . . . . 33 5.2 Efficiency test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 5.2.1 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 5.2.2 Performance evaluation . . . . . . . . . . . . . . . . . . . . . . . . 34 5.3 Case study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 5.3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 5.3.2 Data description . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 5.3.3 Parameter estimation . . . . . . . . . . . . . . . . . . . . . . . . . 37 5.3.4 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 6 Incorporation of the Vehicle Routing Decision 41 6.1 Traveling time factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 6.2 Integrated Model with Traveling time factor . . . . . . . . . . . . . . . . 42 6.3 Vehicle Routing Constraints . . . . . . . . . . . . . . . . . . . . . . . . . 43 6.4 Integrated Model with VRP Constraints . . . . . . . . . . . . . . . . . . 46 7 Conclusion and Future Works 48 Bibliography 50" | |
| dc.language.iso | en | |
| dc.subject | 基因演算法 | zh_TW |
| dc.subject | 設施選址問題 | zh_TW |
| dc.subject | 路徑規劃問題 | zh_TW |
| dc.subject | 週期性需求 | zh_TW |
| dc.subject | 雙層模型 | zh_TW |
| dc.subject | facility location problem | en |
| dc.subject | vehicle routing problem | en |
| dc.subject | periodic demand | en |
| dc.subject | bi-level problem | en |
| dc.subject | genetic algorithm | en |
| dc.title | 考慮需求週期性之服務設施選址與派車規劃 | zh_TW |
| dc.title | Service Facility Location and Vehicle Routing Considering Demand Periodicity | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 黃奎隆(Hsin-Tsai Liu),李家岩(Chih-Yang Tseng) | |
| dc.subject.keyword | 設施選址問題,路徑規劃問題,週期性需求,雙層模型,基因演算法, | zh_TW |
| dc.subject.keyword | facility location problem,vehicle routing problem,periodic demand,bi-level problem,genetic algorithm, | en |
| dc.relation.page | 51 | |
| dc.identifier.doi | 10.6342/NTU202103979 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-10-25 | |
| 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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