vii TABLE OF CONTENTS CHAPTER TITLE PAGE DECLARATION DEDICATION ACKNOWLEDGEMENT ABSTRACT ABSTRAK TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS LIST OF SYMBOLS LIST OF APPENDICES ii iii iv v vi vii x xi xiii xiv xvi 1 INTRODUCTION 1 1.1 Introduction 1 1.2 Research background 2 1.2.1 Job Shop Problem (JSP) 2 1.2.2 Ant Colony Optimization (ACO) 3 1.3 Problem Statement 5 1.4 Objective of the Study 5 1.5 Scope of the Study 6 1.6 Significance of the Study 6 1.7 Thesis Organization 7 2 LITERATURE REVIEW 8 2.1 Introduction 8 2.2 Behaviour of Real Ants 8 2.3 Classical Job Shop Problem 11 2.4 Computational Complexity 13 2.5 Shifting Bottleneck 13
viii 2.6 Review Relevant Research 14 2.7 Research Findings on ACO 17 2.8 Summary 18 3 RESEARCH METHODOLOGY 19 3.1 Introduction 19 3.2 Job Shop Problem 19 3.2.1 Introduction 19 3.2.2 Definition for Job Shop 20 3.2.3 JSP Mathematical Formulation 20 3.2.4 Constraint for the JSP 22 3.2.5 Assumptions for the JSP 23 3.2.6 The JSP Representation 24 3.2.7 Problem Formulation 26 3.2.8 Graph Representation for Job Shop Problem 27 3.3 The Solution Approaches 30 3.3.1 Methodology of Ant Colony Optimization 32 3.3.2 The new ACO-based Algorithm 34 3.3.2.1 Initialization 36 3.3.2.2 The Ant Architecture 36 3.3.2.3 Daemon Action 38 3.3.2.4 Pheromone Update 38 3.3.2.5 Terminating Condition 40 3.4 Summary 40 4 INDUSTRIAL PROBLEM EXPLORATION 41 4.1 Introduction 41 4.2 Introduction to Manufacturing Company 41 4.3 The Manufacturing Framework 42 4.4 Company Problem Description 47 4.5 The Case Study 51 4.6 Sensitivity Analysis 59 4.7 Summary 67 5 IMPLEMENTATION OF ANT COLONY OPTIMIZATION FOR JOB SHOP PROBLEM 68 5.1 Introduction 68 5.2 Development of ACO Algorithm 68
ix 5.3 Algorithm for ACO 70 5.4 Data Diagram 84 5.5 Summary 89 6 SYSTEM DEVELOPMENT FOR ACO SOFTWARE 90 6.1 Introduction 90 6.2 Program Fundamentals 90 6.3 Programming with Microsoft Visual Studio 91 6.4 The Visual Studio Application 92 6.5 Program Visualization 93 6.6 Summary 104 7 ANALYSIS OF RESULTS, CONCLUSION AND RECOM- MENDATION 105 7.1 Introduction 105 7.2 Results 105 7.3 Analyze of The Results 109 7.4 Conclusion 113 7.5 Contribution 114 7.6 Recommendation for Future Research 114 REFERENCES 115 Appendices A 7????
x LIST OF TABLES TABLE NO. TITLE PAGE 2.1 The Instance data with 3 machines and 3 jobs. 12 2.2 Relevant Research on Ant Colony Optimization. 15 2.3 Relevant Research on Job Shop Problem. 16 2.4 Relevant Research on Job Shop Scheduling Problem in Ant Colony Optimization. 17 3.1 The Processing Time for 2/3/G/C max job shop problem. 29 4.1 The Processing Time for 2/3/G/C max job shop problem. 57 4.2 Random values of C max and makespan depending on the parameter values of α, β and ρ. 60 4.3 Random values of C max and makespan depend on the values of β parameters, when ρ = 0. 61 4.4 Random value of C max and makespan depending on the values of β parameters, when ρ = 1 and α = 0. 62 4.5 Random values of C max and makespan depend on the values of β parameters, when ρ = 2. 63 4.6 Random values of C max and makespan depend on the values of β parameters, when ρ = 1 and α = 1. 64 4.7 Random values of C max and makespan depend on the values of ρ parameters, when β = 0. 65 4.8 Random values of C max and makespan depend on the values of ρ parameters, when β = 1. 66 5.1 Short caption 85 7.1 The Stimulation Results. 110 7.2 Results for makespan with 6 machines. 110 7.3 Comparison the results between Shifting Bottleneck Heuristic Method [1] with the new ACO-based Algorithm. 112
xi LIST OF FIGURES FIGURE NO. TITLE PAGE 2.1 Ant experimental for the bridge experiment. 9 2.2 The ants are moving on the straight line. 9 2.3 An unexpected obstacle has interrupted the initial path. 10 2.4 The same situation on the other side of the obstacle. 10 2.5 Visual of ants choosing the shorter path. 11 3.1 The definition of a 2/3/G/C max job shop problem into graph. 28 3.2 The result for a 2/3/G/C max job shop problem into graph. 30 3.3 The flow chart for work explanation. 32 3.4 The problem solving step. 33 4.1 The framework for the warehouse process. 43 4.2 The typical job shop layout problem that forms the case study. 44 4.3 The data for the product customized E07 rack. 48 4.4 The processing time for the product. 49 4.5 The data input with 6 machine. 50 4.6 The graph for input data Power Press proses. 52 4.7 The graph for input data Tapping process. 53 4.8 The graph for input data Clinching Process. 54 4.9 The graph for input data Bending Process. 55 4.10 The graph for input data Machining Process. 56 4.11 The total number of edges versus total number of jobs run on 6 machines. 57 4.12 The total number of edges versus total number of nodes and operations. 58 4.13 The graph on sensitivity analysis for Table 3. 61 4.14 The graph for Sensitivity analysis for Table 4.4. 62 4.15 The graph for sensitivity analysis for Table 5.5. 63 4.16 The graph for sensitivity analysis for Table 6. 64 4.17 The graph for sensitivity analysis for Table 7. 65
xii 4.18 The graph for sensitivity analysis for Table 4.8. 66 5.1 The Pseudocode of ACO algorithm. 68 5.2 The framework for the proposed ACO algorithm. 70 5.3 The Gantt Diagram for the Power Press Process. 86 5.4 The Gantt Diagram for the Tapping Process. 86 5.5 The Gantt Diagram for the Clinching Process. 87 5.6 The Gantt Diagram for the Bending Process. 88 5.7 The Gantt Diagram for the Machining Process. 88 6.1 The Welcome GUI for the program. 93 6.2 The Project Properties for the Case Study. 94 6.3 The Input Data for the CNC Machining. 95 6.4 The Input Data for the Bending process. 96 6.5 The Input Data for the Clinching process. 97 6.6 The Input Data for the Tapping process. 98 6.7 The Input Data for the Power Press process. 99 6.8 The Results for the case study. 100 6.9 The Debug for the case study. 101 6.10 The flow run for the software development. 103 7.1 The consequence for Power Press Process. 106 7.2 The Consequence for Tapping Process. 106 7.3 The Consequence for Clinching Process. 107 7.4 The consequence for Bending Process. 108 7.5 The consequence for CNC Machining Process. 109
xiii LIST OF ABBREVIATIONS ACO Ant Colony Optimization JSP Job Shop Problem Np-hard Non-deterministic Polynomial Time Hard TSP Traveling Salesman Problem
xiv LIST OF SYMBOLS C max Makespan / total completion time m Total of machine n Total of job i node i j node j M m m Machine J n n Job J j Jobs at node j O ij Operation at node i and node j P ij Processing Time s Source Node t Sink Node λ Wavelength α Real positive parameters β Real positive parameters ρ Evaporation rate γ Decision variable, generates a sequence O Operations η ij Heuristic value associates with the common C ij τ ij Pheromone value at node i and j d ij Heuristic distance between node i and j G A representative of a graph Sij e Empty Solution
xv S g Good solution L k Tour length of the k-th ant
xvi LIST OF APPENDICES APPENDIX TITLE PAGE