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研究生： 陳亮都
Liang-Tu Chen
論文名稱： 需求與價格及時間相依下銷售與採購/生產協同規劃之研究
Collaborative Marketing and Procurement/Production Planning with Price-Dependent and Time-Varying Demand
指導教授： 陳振明
Jen-Ming Chen
口試委員:
學位類別： 博士
Doctor
系所名稱： 管理學院 - 工業管理研究所
Graduate Institute of Industrial Management
畢業學年度： 94
語文別： 英文
論文頁數： 121
中文關鍵詞： 行銷 、採購 、生產 、動態規劃 、跨部門整合 、耗損性
外文關鍵詞： Marketing, procurement, production, dynamic programming, inter-functional coordination, deterioration
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    • 雖然目前時下所提供的資訊管理技術與系統可做為整合企業資源配置、規劃與管理的平台，然而在銷售與採購/生產規劃之間的決策仍然維持相當分離，無法相互整合。此大部分乃導因於這些技術與系統的參數不是固定就是隨意選取，造成參數的設定很少是有效，而且在一般的系統設定上均假設生產產能為無限，此與企業實際運作並不相符。本研究乃在同時考量產能有限性，需求為價格與時間函數，銷售價格、生產成本與生產率隨時間改變，以及允許缺貨下之耗損性商品，藉由雙變數最佳化模式、動態規劃技術及迭代法，發展一套整合企業銷售與採購/生產規劃之戰術性決策支援模式，以改善生產規劃靜態參數設定與市場動態特性間的差距，使後端生產決策更能反映前端市場變化，以達企業總利潤最大化。另外，在每一存貨週期，我們依顧客需求將生產系統分為兩種類型：一為 “缺貨跟隨存貨” 之問題，亦即IFS(Inventory Followed by Shortages)；另一為 “存貨跟隨缺貨” 之問題，亦即SFI(Shortages Followed by Inventory)。本研究在IFS和SFI二種生產系統下，同時發展協同式決策與分散式決策二種模型，以及進行數值分析，以便進一步瞭解不同採購/生產系統與不同決策模型對企業利潤及存貨投資影響之顯著程度。本研究最後提供國內頗具規模之零售業連鎖店生魚片的例子，具體說明本研究所建構模式與流程之特性與行為，以及其在實務界之應用與管理意涵。

    Although the evolving information management technologies provide a unified platform for managing and integrating core business processes within a firm, the decision-making between marketing and procurement/production planning remains loosely dependent. It is due in large part to the inherent weaknesses of the technologies such as fixed and static parameters settings and uncapacitated assumption. To remedy these drawbacks, we propose optimal decision models that solve the replenishment/production lot-size problem taking into account the dynamic aspects of customer’s demand. More specifically, we consider a single continuous decay product in a periodic review inventory system where shortages are allowed and fully backlogged. The demand of such product is assumed to be a multivariate function, depending solely on price and time. Unlike previous research, upward or downward adjustment of the selling price can be made at each review epoch. The objective of this research is to determine the periodic selling price and lot-size over multi-period planning horizon so that the total profit is maximized. The problems are formulated as dynamic programming models and solved by numerical search techniques. The models can be used as an add-on optimizer that coordinates distinct functions with the objective of maximizing total profit. Special emphasis is placed on the comparative study between the proposed optimization models that are based on the coordinated and decentralized policies, and the inventory followed by shortages (IFS) and shortages followed by inventory (SFI) replenishment/production systems. To even more understand the properties and behaviors of the proposed model and solution procedure, a real case study for sliced raw fishes at a local supermarket of a large national retail chain is carried out.

    中文摘要 I ABSTRACT II ACKNOWLEDGMENTS III TABLE OF CONTENTS IV LIST OF FIGURES VI LIST OF TABLES VII NOTATIONS VIII CHAPTER 1 INTRODUCTION 1 1.1 MOTIVATION 1 1.2 OBJECTIVES 2 1.3 ORGANIZATION 5 CHAPTER 2 LITERATURE REVIEW 8 2.1 CROSS-FUNCTIONAL INTEGRATION 8 2.2 DETERIORATING ITEM 12 2.3 DEMAND FUNCTION 14 CHAPTER 3 COLLABORATIVE MARKETING AND PROCUREMENT PLANNING WITH IFS SYSTEM 18 3.1 PROBLEM DESCRIPTION AND ASSUMPTIONS 18 3.2 THE MODEL AND SOLUTION PROCEDURES 20 3.2.1 The Decentralized Policy 24 3.2.1.1 Decentralized Pricing with Shortages 24 3.2.1.2 Decentralized Pricing without Shortages 25 3.2.2 The Coordinated Policy 25 3.2.2.1 Coordinated Pricing with Shortages 25 3.2.2.2 Coordinated Pricing without Shortages 27 3.3 IMPLEMENTATION AND SENSITIVITY ANALYSIS 27 3.3.1 Illustrative Examples and Comparative Study 28 3.3.1.1 Time-Decreasing Demand 28 3.3.1.2 Time-Increasing Demand 29 3.3.2 Sensitivity Analysis 31 3.4 SUMMARY 32 CHAPTER 4 COLLABORATIVE MARKETING AND PROCUREMENT PLANNING WITH SFI SYSTEM 33 4.1 PROBLEM DESCRIPTION AND ASSUMPTIONS 33 4.2 THE MODEL AND SOLUTION PROCEDURES 34 4.2.1 The Decentralized Policy 36 4.2.2 The Coordinated Policy 40 4.3 IMPLEMENTATION AND SENSITIVITY ANALYSIS 42 4.3.1 Illustrative Examples and Comparative Study 43 4.3.2 Sensitivity Analysis 46 4.4 SUMMARY 48 CHAPTER 5 COLLABORATIVE MARKETING AND PRODUCTION PLANNING WITH IFS SYSTEM 49 5.1 PROBLEM DESCRIPTION AND ASSUMPTIONS 49 5.2 THE MODEL AND SOLUTION PROCEDURES 50 5.2.1 The Decentralized Policy 53 5.2.2 The Coordinated Policy 57 5.3 IMPLEMENTATION AND SENSITIVITY ANALYSIS 59 5.3.1 An Illustrative Example 60 5.3.2 Comparative Study of Decentralized and Coordinated Policies 62 5.3.3 Sensitivity Analysis 63 5.4 SUMMARY 64 CHAPTER 6 COLLABORATIVE MARKETING AND PRODUCTION PLANNING WITH SFI SYSTEM 66 6.1 PROBLEM DESCRIPTION AND ASSUMPTIONS 66 6.2 THE MODEL AND SOLUTION PROCEDURES 67 6.2.1 The Decentralized Policy 70 6.2.2 The Coordinated Policy 72 6.3 IMPLEMENTATION AND SENSITIVITY ANALYSIS 73 6.3.1 An Illustrative Example 74 6.3.2 Comparative Study of Decentralized and Coordinated Policies 76 6.3.3 Sensitivity Analysis 77 6.4 COMPARATIVE STUDY OF IFS AND SFI PRODUCTION SYSTEMS 77 6.5 SUMMARY 82 CHAPTER 7 A CASE STUDY 84 7.1 CASE DESCRIPTION 84 7.2 NUMERICAL STUDY 85 7.3 SENSITIVITY ANALYSIS 87 7.4 SUMMARY 89 CHAPTER 8 CONCLUSIONS AND FUTURE RESEARCH 90 8.1 CONCLUSIONS 90 8.2 FUTURE RESEARCH 91 REFERENCES 93 APPENDICES 103 BIOGRAPHICAL SKETCH 116 A. JOURNAL PAPERS 116 B. CONFERENCE PAPERS 117 C. TECHNICAL REPORT AND OTHERS 118 D. PROJECTS 119 RESPONSE TO COMMITTEE 120

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