TABLE OF CONTENTS TABLE OF CONTENTS COVER PAGE HALAMAN PENGESAHAN PERNYATAAN NASKAH SOAL TUGAS AKHIR ACKNOWLEDGEMENT FOREWORD

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1 TABLE OF CONTENTS TABLE OF CONTENTS COVER PAGE HALAMAN PENGESAHAN PERNYATAAN NASKAH SOAL TUGAS AKHIR ACKNOWLEDGEMENT FOREWORD TABLE OF CONTENTS LIST OF FIGURES LIST OF TABLES LIST OF APPENDICES LIST OF NOTATIONS AND ABBREVIATIONS ABSTRACT i ii iii iv v vi ix xi xiii xiv xv xvii CHAPTER I INTRODUCTION Background Problem Statement Scopes and Assumptions Research Purposes Research Benefits 5 CHAPTER II LITERATURE REVIEW 6 CHAPTER III THEORY Supply Chain Management Deterministic Demand Vehicle Routing Problem Mathematical Programming Integer Programming (IP) Solution Methods for VRP Genetic Algorithm Genetic Algorithm for VRP 19 ix

2 x 3.9 Ant Colony Optimization Slovin s Formula Normality Test Mann-Whitney U Test / Wilcoxon Rank-Sum Test Design of Experiments (DoE) Factorial Experiments Regression Analysis 25 CHAPTER IV RESEARCH METHODOLOGY Research Design Research Object Research Tools Data Collection Research Framework Data Processing Initial Data Design of Experiments (DoE) Developed Model for Genetic Algorithm (GA) Developed Model for Ant Colony Optimization (ACO) 35 CHAPTER V RESULTS AND DISCUSSIONS Distribution Process at SNS Branch Yogyakarta Mathematical Model Validation Data Validation Model Validation Distribution Process Scenario Route Optimization Using GA and ACO Design of Experiments (DoE) for GA and ACO Result Comparison GA Optimization by K-means Clustering 61 CHAPTER VI CONCLUSIONS AND RECOMMENDATIONS Conclusions Recommendations 68 REFERENCES 69 APPENDICES 72

3 LIST OF FIGURES Figure 1.1 Value Chain of a Company in General Figure 1.2 Fuel Cost for Jan Mar 2015 Figure 3.1 Supply Chain Stage Figure 3.2 A solution to a VRP Figure 3.3 Example of Initial Population Figure 3.4 Roulette Wheel Selection Method Figure 3.5 Crossover Operator Figure 3.6 Mutation Operator Figure 3.7 The illustration of ACO Figure 4.1 Research Framework Figure 4.2 Data Processing Figure 4.3 Genetic Algorithm (GA) Process Figure 4.4 Example of Initial Population Figure 4.5 The example of Crossover Figure 4.6 The example of Mutation Figure 4.7 Ant Colony Optimization (ACO) Process Figure 5.1 SNS Distribution Network in Indonesia Figure 5.2 Distribution Process at SNS Yogyakarta Figure 5.3 Kolmorov-smirnov Test Figure 5.4 Mann-Whitney Test Results Figure 5.5 Simple Pseudo Code for Genetic Algorithm (GA) Figure 5.6 Simple Pseudo Code for Ant Colony Optimization (ACO) Figure 5.7 Main Interface for Data Loaded for VRP Optimization Figure 5.8 Interface for GA Optimization Figure 5.9 The Graph of Fitness (1,000 Generations) xi

4 xii Figure 5.10 The Graph of Fitness (300 Convergence Values) Figure 5.11 Interface for ACO Optimization Figure 5.12 Regression Analysis Result for GA Figure 5.13 Regression Analysis Result for ACO Figure 5.14 Comparison between Existing vs GA vs ACO Figure 5.15 Route for Gunung Kidul Region (GA) Figure 5.16 Comparison of Fuel Cost Figure 5.17 Route for VH13 Figure 5.18 Load Percentage of Each Vehicle Figure 5.19 Total Time for All Solutions

5 LIST OF TABLES Table 2.1 Summary of Previous Research Table 2.2 Research Mapping Table 4.1 Level DoE for Genetic Algorithm (GA) Table 4.2 Level DoE for Ant Colony Optimization (ACO) Table 5.1 Index of Mathematical Model Table 5.2 Parameter of Mathematical Model Table 5.3 Decision Variable of Mathematical Model Table 5.4 Delivery Scenario for Each Vehicle Table 5.5 Level DoE for Genetic Algorithm (GA) Table 5.6 Level DoE for Ant Colony Optimization (ACO) Table 5.7 The Optimal Parameter Values for GA Table 5.8 The Optimal Parameters Values for ACO Table 5.9 The Results of GA and ACO Table 5.10 Total Fuel Cost for Each Vehicle Table 5.11 Time Calculation in Delivery Process (Existing Condition) Table 5.12 Time Calculation in Delivery Process (GA) Table 5.13 Time Calculation in Delivery Process (ACO) Table 5.14 The Centroid of Each Cluster Table 5.15 The Result of GA with K-means Clustering Table 5.16 Total Fuel Cost for GA-Kmeans Table 5.17 Time Calculation in Delivery Process (GA+K-means) xiii

6 LIST OF APPENDICES Appendix 1. List of Customers Appendix 2. List of Products Appendix 3. List of Vehicles Appendix 4. List of Total Demand Appendix 5. List of Detailed Demand Appendix 6. Fuel Cost Data Appendix 7. Replication of GA Appendix 8. Replication of ACO Appendix 9. Matlab Code Appendix 10. Maps xiv

7 LIST OF NOTATIONS AND ABBREVIATIONS ACO CVRP DC DoE GA KPI OFR SCM SNS k s N α H F R Pm Px β τ ρ Z I J K : Ant Colony Optimization : Capacitated Vehicle Routing Problem : Distribution Center : Design of Experiments : Genetic Algorithm : Key Performance Indicator : Order Fulfillment Rate : Supply Chain Management : Sinar Niaga Sejahtera : Level of Factor : Number of Sample : Number of Population : level of significance : Hyphothesis : Fitness : Random Number : Mutation Probability : Crossover Probability : Trace s effect : Pheromone : Evaporation Rate : Objective Function : Index of predecessor customer (i J) : Index of successor customer (j J) : Index of product (k K) xv