Autonomous Guided Vehicles (eBook)

Preface 6
Acknowledgments 9
Contents 10
Models for AGVs’ Scheduling and Routing 13
1.1 Summary 13
1.2 Scheduling Models 14
1.2.1 Artificial Intelligence 14
1.2.2 Simulation 15
1.3 Routing Models 16
1.3.1 Artificial Intelligent 17
1.3.2 Simulation 20
1.4 Conclusions 24
References 25
Analytical Material Flow Model for AGVSystem 28
2.1 Summary 28
2.2 Statement of the Problem 30
2.3 Mathematical Model 31
2.3.1 Regression Model for Performance Analysis 33
2.4 Conclusions 35
References 36
Nonlinear Stochastic Model for AGV System 37
3.1 Summary 37
3.2 Statement of the Problem 39
3.3 Mathematical Model 40
3.3.1 Successive Linear Programming Approach 42
3.4 Conclusions 47
References 48
Reliability Model for AGV 50
4.1 Summary 50
4.2 Statement of the Problem 53
4.3 Mathematical Model 54
4.3.1 Reliability Component 54
4.3.2 Perceptron Neural Network 58
4.4 Conclusions 62
References 63
Uncertain Optimal Path for AGV System 66
5.1 Summary 66
5.2 Statement of the Problem 68
5.3 Mathematical Modeling 69
5.3.1 Fuzzy Logic and Membership Functions 69
5.3.2 Fuzzy Systems 71
5.3.3 Modeling the Proposed Fuzzy Problem 73
5.3.4 Operations on the Parameters of the Problem:Normalization of the Parameters 74
5.3.5 Weighing the Parameters 77
5.3.6 Construction of the Hierarchy 77
5.3.7 Priority Setting 77
5.3.8 Consistency Check 78
5.3.9 Ranking of Triangular Fuzzy Numbers 81
5.3.10 Shortest Path in a Network 82
5.4 Conclusions 84
References 84
Cross Entropy Model for AGV Routing Time 87
6.1 Summary 87
6.2 Statement of the Problem 90
6.3 Mathematical Model 91
6.3.1 Cross Entropy (CE) 94
6.4 Conclusions 98
References 98
Neuro-Fuzzy-Regression Expert System forAGV Optimal Path 100
7.1 Summary 100
7.2 Statement of the Problem 103
7.3 Mathematical Model 105
7.3.1 Artificial Neural Network 107
7.3.2 The Backpropagation Neural Network 110
7.3.3 Fuzzy Logic 113
7.3.4 Mamdani Fuzzy System 114
7.3.5 Multiple Linear Regression 115
7.3.6 Shortest Path in a Network 117
7.3.7 Dynamic Programming 117
7.4 Conclusions 119
References 119
Optimal Path for AGV System with IntelligentAgents 123
8.1 Summary 123
8.2 Statement of the Problem 126
8.3 Mathematical Model 132
8.3.1 Normalization Process 134
8.4 Conclusions 136
References 136
Earliness/Tardiness for a Multiple AGV System 139
9.1 Summary 139
9.2 Statement of the Problem 142
9.3 Mathematical Model 144
9.4 Conclusions 150
References 150
Markovian Model for Multiple AGV System 153
10.1 Summary 153
10.2 Statement of the Problem 157
10.3 Mathematical Model 159
10.4 Conclusions 172
References 172
Producer's Behavior Analysis for AGV System 175
11.1 Summary 175
11.2 Statement of the Problem 177
11.3 Mathematical Model 179
11.4 Conclusions 190
References 191
Risk for Multiple AGV System 195
12.1 Summary 195
12.2 Statement of the Problem 198
12.3 Mathematical Model 200
12.4 Conclusions 208
References 209