Sven Axsäter. Inventory Control. Third Edition. Springer

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Transcription:

Sven Axsäter Inventory Control Third Edition Springer

Contents 1 Introduction 1 1.1 Importance and Objectives of Inventory Control 1 1.2 Overview and Purpose of the Book 2 1.3 Framework 4 2 Forecasting 7 2.1 Objectives and Approaches 7 2.2 Demand Models 8 2.2.1 Constant Model 9 2.2.2 Trend Model 9 2.2.3 Trend-seasonal Model 10 2.2.4 Choosing Demand Model 10 2.3 Moving Average 11 2.4 Exponential Smoothing 11 2.4.1 Updating Procedure 11 2.4.2 Comparing Exponential Smoothing to a Moving Average 12 2.4.3 Practical Considerations and an Example 13 2.5 Exponential Smoothing with Trend 15 2.5.1 Updating Procedure 15 2.5.2 Practical Considerations and an Example 16 2.6 Winters'Trend-seasonal Method 17 2.6.1 Updating Procedure 17 2.6.2 Practical Considerations and an Example 18 2.7 Using Regression Analysis 19 2.7.1 Forecasting Demand for a Trend Model 19 2.7.2 Practical Considerations and an Example 20 2.7.3 Forecasts Based on Other Factors 21 2.7.4 More General Regression Models 22 2.8 Sporadic Demand 23 2.9 Box-Jenkins Techniques 23 2.10 Forecast Errors 25 2.10.1 Common Error Measures 25 2.10.2 Updating MAD or a 2 26 vii

viii Contents 2.10.3 Determining the Standard Deviation as a Function of Demand 27 2.10.4 Forecast Errors for Other Time Periods 28 2.10.5 Sales Data Instead of Demand Data 29 2.11 Monitoring forecasts 29 2.11.1 Checking Demand 30 2.11.2 Checking that the Forecast Represents the Mean 30 2.12 Manual forecasts 31 Problems 32 3 Costs and Concepts 37 3.1 Considered Costs and Other Assumptions 37 3.1.1 Holding Costs 38 3.1.2 Ordering or Setup Costs 38 3.1.3 Shortage Costs or Service Constraints 38 3.1.4 Other Costs and Assumptions 39 3.2 Different Ordering Systems 39 3.2.1 Inventory Position 39 3.2.2 Continuous or Periodic Review 40 3.2.3 Different Ordering Policies 41 3.2.3.1 {R, Q) Policy 41 3.2.3.2 (s, S) Policy 42 4 Single-Echelon Systems: Deterministic Lot Sizing 45 4.1 The Classical Economic Order Quantity Model 45 4.1.1 Optimal Order Quantity 45 4.1.2 Sensitivity Analysis 47 4.1.3 Reorder Point 48 4.2 Finite Production Rate 48 4.3 Quantity Discounts 49 4.4 Backorders Allowed 51 4.5 Time-Varying Demand 53 4.6 The Wagner-Whitin Algorithm 54 4.7 The Silver-Meal Heuristic 57 4.8 A Heuristic that Balances Holding and Ordering Costs 59 4.9 Exact or Approximate Solution 60 Problems 60 5 Single-Echelon Systems: Reorder Points 65 5.1 Discrete Stochastic Demand 65 5.1.1 Compound Poisson Demand 65 5.1.2 Logarithmic Compounding Distribution 68 5.1.3 Geometrie Compounding Distribution 69 5.1.4 Smooth Demand 70 5.1.5 Fitting Discrete Demand Distributions in Practice 71

Contents ix 5.2 Continuous Stochastic Demand 72 5.2.1 Normally Distributed Demand 72 5.2.2 Gamma Distributed Demand 72 5.3 Continuous Review (R, Q) Policy Inventory Level Distribution. 74 5.3.1 Distribution of the Inventory Position 74 5.3.2 An Important Relationship 75 5.3.3 Compound Poisson Demand 76 5.3.4 Normally Distributed Demand 76 5.4 Service Levels 79 5.5 Shortage Costs 80 5.6 Determining the Safety Stock for Given Si 80 5.7 Fill Rate and Ready Rate Constraints 81 5.7.1 Compound Poisson Demand 81 5.7.2 Normally Distributed Demand 82 5.8 Fill Rate-a Different Approach 83 5.9 Shortage Cost per Unit and Time Unit 84 5.9.1 Compound Poisson Demand 85 5.9.2 Normally Distributed Demand 86 5.10 Shortage Cost per Unit 88 5.11 Continuous Review (s, S) Policy 89 5.12 Periodic Review-Fill Rate 91 5.12.1 Basic Assumptions 91 5.12.2 Compound Poisson Demand-(/?, Q) Policy 92 5.12.3 Compound Poisson Demand-(s, S) Policy 93 5.12.4 Normally Distributed Demand-(R, Q) Policy 94 5.13 The Newsboy Model 95 5.14 A Model with Lost Sales 97 5.15 Stochastic Lead-times 99 5.15.1 Two Types of Stochastic Lead-times 99 5.15.2 Handling Sequential Deliveries Independent of the Lead-time Demand 100 5.15.2.1 Handling Independent Lead-Times 101 5.15.3 Comparison of the Two Types of Stochastic Lead-Times 102 Problems 103 6 Single-Echelon Systems: Integration-Optimality 107 6.1 Joint Optimization of Order Quantity and Reorder Point 107 6.1.1 Discrete Demand 107 6.1.1.1 (R,Q) Policy 107 6.1.1.2 (s, S) Policy 109 6.1.2 An Iterative Technique 110 6.1.3 Fill Rate Constraint: A Simple Approach 111 6.2 Optimality of Ordering Policies 113 6.2.1 Optimality of (R, Q) Policies When Ordering in Batches 113 6.2.2 Optimality of (s, S) Policies 115 6.3 Updating Order Quantities and Reorder Points in Practice 116 Problems 119

x Contents 7 Coordinated Ordering 121 7.1 Powers-of-Two Policies 121 7.2 Production Smoothing 125 7.2.1 The Economic Lot Scheduling Problem (ELSP) 126 7.2.1.1 Problem Formulation 126 7.2.1.2 The Independent Solution 127 7.2.1.3 Common Cycle Time 128 7.2.1.4 Bomberger's Approach 129 7.2.1.5 A Simple Heuristic 130 7.2.1.6 Other Problem Formulations 132 7.2.2 Time-Varying Demand 133 7.2.2.1 A Generalization of the Classical Dynamic Lot Size Problem 133 7.2.2.2 Application of Mathematical Programming Approaches 134 7.2.3 Production Smoothing and Batch Quantities 135 7.3 Joint Replenishments 137 7.3.1 A Deterministic Model 137 7.3.1.1 Approach 1. An Iterative Technique 138 7.3.1.2 Approach 2. Roundy's 98 % Approximation.. 140 7.3.2 A Stochastic Model 143 Problems 144 8 Multi-Echelon Systems: Structures and Ordering Policies 147 8.1 Inventory Systems in Distribution and Production 147 8.1.1 Distribution Inventory Systems 148 8.1.2 Production Inventory Systems 149 8.1.3 Repairable Items 150 8.1.4 Lateral Transshipments in Inventory Systems 151 8.1.5 Inventory Models with Remanufacturing 152 8.2 Different Ordering Systems 153 8.2.1 Installation Stock Reorder Point Policies and KANBAN Policies 154 8.2.2 Echelon Stock Reorder Point Policies 154 8.2.3 Comparison of Installation Stock and Echelon Stock Policies 156 8.2.4 Material Requirements Flanning 160 8.2.5 Ordering System Dynamics 167 Problems 168 9 Multi-Echelon Systems: Lot Sizing 171 9.1 Identical Order Quantities 172 9.1.1 Infinite Production Rates 172 9.1.2 Finite Production Rates 172

Contents xi 9.2 Constant Demand 173 9.2.1 A. Simple Serial System with Constant Demand 174 9.2.2 Roundy's 98 % Approximation 178 9.3 Time-Varying Demand 182 9.3.1 Sequential Lot Sizing 182 9.3.2 Sequential Lot Sizing with Modified Parameters 184 9.3.3 Other Approaches 186 9.4 Concluding Remarks 187 Problems 187 10 Multi-Echelon Systems: Reorder Points 191 10.1 The Clark-Scarf Model 192 10.1.1 Serial System 192 10.1.2 The Clark-Scarf Approach for a Distribution System... 198 10.2 The METRIC Approach for Distribution Systems 201 10.3 Two Exact Techniques 205 10.3.1 Disaggregation of Warehouse Backorders 205 10.3.2 A Recursive Procedure 206 10.4 Optimization of Ordering Policies 208 10.5 Batch-Ordering Policies 210 10.5.1 Serial System 210 10.5.2 Distribution System 212 10.5.2.1 Some Basic Results 213 10.5.2.2 METRIC Type Approximations 214 10.5.2.3 Disaggregation of Warehouse Backorders... 215 10.5.2.4 Following Supply Units through the System.. 215 10.5.2.5 Practical Considerations 216 10.6 Other Assumptions 217 10.6.1 Guaranteed Service Model Approach 217 10.6.2 Coordination and Contracts 218 10.6.2.1 The Newsboy Problem with Two Firms 219 10.6.2.2 Wholesale-Price Contract 219 10.6.2.3 Buyback Contract 221 Problems 221 11 Implementation 223 11.1 Preconditions for Inventory Control 223 11.1.1 Inventory Records 223 11.1.1.1 Updating Inventory Records 224 11.1.1.2 Auditing and Correcting Inventory Records... 225 11.1.2 Performance Evaluation 226 11.2 Development and Adjustments 227 11.2.1 Determine the Needs 227 11.2.2 Selective Inventory Control 228 11.2.3 Model and Reality 229

xii Contents 11.2.4 Step-by-Step Implementation 230 11.2.5 Simulation 231 11.2.6 Short-Run Consequences of Adjustments 231 11.2.7 Education 232 Appendix 1 235 Appendix 2 247 References 253 Index 265