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研究生: 郝俊傑
RIZKY FEBRI IBRA HABIBIE
論文名稱: 考量動態需求之智慧販賣機產品選擇、貨架展示與補貨最佳化模型
A joint optimization model for product selection, shelf display, and replenishment considering dynamic demands for smart vending machines
指導教授: 王孔政
Kung-Jeng Wang
口試委員: 曹譽鐘
Yu-Chung Tsao
喻奉天
Vincent F. Yu
學位類別: 碩士
Master
系所名稱: 管理學院 - 工業管理系
Department of Industrial Management
論文出版年: 2023
畢業學年度: 111
語文別: 英文
論文頁數: 56
中文關鍵詞: 智能售貨機商品選擇貨架展示補貨週期遺傳算法
外文關鍵詞: Smart vending machine, product selection, shelf display, replenishment cycle, genetic algorithm
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  • 智能自動售貨機(SVM)是一個微型市場,為產品銷售創造靈活性; 然而,針對動態需求的產品選擇、貨架展示和補貨決策對於 SVM 的卓越運營至關重要且具有挑戰性。 本研究開發了支持向量機聯合決策的數學模型。 該模型採用混合整數非線性規劃來製定,以實現利潤最大化。 該模型經過修改,在決定補貨計劃時納入缺貨成本。 所提出的模型是使用遺傳算法求解的。 通過與各種數據集進行比較,結果顯示這些算法的有效性和效率。


    Smart vending machine (SVM) is a micro market that creates flexibility for product sale; however, product selection, shelf display, and replenishment decisions against dynamic demands are essential and challenging to the SVM operation excellence. This study develops a mathematical model for the joint decisions of the SVM. The model was formulated in mixed integer non-linear programming to maximize profit. The model was modified to incorporate stock-out costs while deciding on a replenishment plan. The proposed model is solved using a genetic algorithm. The results show the effectiveness and efficiency of these algorithms by comparing them with a variety of data sets.

    CONTENTS 摘要 ABSTRACT ACKNOWLEDGEMENT CONTENTS FIGURE LISTS TABLE LISTS CHAPTER 1 INTRODUCTION CHAPTER 2 LITERATURE REVIEW CHAPTER 3 MODELING AND SOLUTION APPROACH 3.1 Modelling 3.2 Solution approach CHAPTER 4 EXPERIMENTS AND DISCUSSION 4.1 Parameter setting 4.2 Comparison of solution algorithms 4.3 Sensitivity analysis 4.3.1 Space elasticity 4.3.2 Cross elasticity 4.3.3 Demand fluctuation 4.3.4 Stock-out cost CHAPTER 5 CONCLUSION REFERENCES APPENDIX A. Tabu search B. Small datasets C. Medium datasets D. Large datasets E. Products set

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    全文公開日期 2024/08/07 (國家圖書館:臺灣博碩士論文系統)
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