Adaptive Business Intelligence

Contents
Part I: Complex Business Problems
1 Introduction........................................................................................... 3
2 Characteristics of Complex Business Problems..................................... 9
2.1 Number of Possible Solutions...................................................... 10
2.2 Time-Changing Environment ...................................................... 12
2.3 Problem-Specific Constraints ...................................................... 13
2.4 Multi-objective Problems ............................................................ 14
2.5 Modeling the Problem................................................................. 16
2.6 A Real-World Example ............................................................... 19
3 An Extended Example: Car Distribution............................................ 25
3.1 Basic Terminology...................................................................... 25
3.2 Off-lease Cars ............................................................................. 27
3.3 The Problem ............................................................................... 28
3.4 Transportation............................................................................. 30
3.5 Volume Effect............................................................................. 32
3.6 Price Depreciation and Inventory................................................. 33
3.7 Dynamic Market Changes ........................................................... 33
3.8 The Solution ............................................................................... 34
4 Adaptive Business Intelligence............................................................. 37
4.1 Data Mining................................................................................ 38
4.2 Prediction.................................................................................... 41
4.3 Optimization ............................................................................... 43
4.4 Adaptability ................................................................................ 44
4.5 The Structure of an Adaptive Business Intelligence System.......... 45
Part II: Prediction and Optimization
5 Prediction Methods and Models .......................................................... 49
5.1 Data Preparation.......................................................................... 51
5.2 Different Prediction Methods ...................................................... 56
5.2.1 Mathematical Methods .................................................... 56
5.2.2 Distance Methods............................................................ 62
5.2.3 Logic Methods ................................................................ 64
5.2.4 Modern Heuristic Methods .............................................. 68
5.2.5 Additional Considerations ............................................... 69
5.3 Evaluation of Models .................................................................. 69
5.4 Recommended Reading............................................................... 74
6 Modern Optimization Techniques....................................................... 75
6.1 Overview .................................................................................... 75
6.2 Local Optimization Techniques ................................................... 82
6.3 Stochastic Hill Climber ............................................................... 87
6.4 Simulated Annealing................................................................... 90
6.5 Tabu Search ................................................................................ 96
6.6 Evolutionary Algorithms............................................................ 101
6.7 Constraint Handling ................................................................... 108
6.8 Additional Issues........................................................................ 112
6.9 Recommended Reading.............................................................. 114
7 Fuzzy Logic ......................................................................................... 117
7.1 Overview ................................................................................... 119
7.2 Fuzzifier .................................................................................... 119
7.3 Inference System........................................................................ 123
7.4 Defuzzifier ................................................................................. 127
7.5 Tuning the Membership Functions and Rule Base....................... 128
7.6 Recommended Reading.............................................................. 129
8 Artificial Neural Networks ................................................................. 131
8.1 Overview ................................................................................... 132
8.2 Node Input and Output ............................................................... 134
8.3 Different Types of Networks ...................................................... 136
8.3.1 Feed-Forward Neural Networks...................................... 137
8.3.2 Recurrent Neural Networks ............................................ 140
8.4 Learning Methods ...................................................................... 142
8.4.1 Supervised Learning....................................................... 142
8.4.2 Unsupervised Learning................................................... 146
8.5 Data Representation ................................................................... 147
8.6 Recommended Reading.............................................................. 148
9 Other Methods and Techniques.......................................................... 151
9.1 Genetic Programming................................................................. 151
9.2 Ant Systems and Swarm Intelligence.......................................... 158
9.3 Agent-Based Modeling............................................................... 163
9.4 Co-evolution .............................................................................. 169
9.5 Recommended Reading.............................................................. 173
Part III: Adaptive Business Intelligence
10 Hybrid Systems and Adaptability....................................................... 177
10.1 Hybrid Systems for Prediction.................................................... 178
10.2 Hybrid Systems for Optimization ............................................... 183
10.3 Adaptability ............................................................................... 187
11 Car Distribution System ..................................................................... 191
11.1 Overview ................................................................................... 192
11.2 Graphical User Interface............................................................. 194
11.2.1 Constraint Handling ....................................................... 195
11.2.2 Reporting....................................................................... 201
11.3 Prediction Module...................................................................... 203
11.4 Optimization Module ................................................................. 206
11.5 Adaptability Module .................................................................. 208
11.6 Validation .................................................................................. 211
12 Applying Adaptive Business Intelligence............................................ 215
12.1 Marketing Campaigns ................................................................ 215
12.2 Manufacturing............................................................................ 221
12.3 Investment Strategies ................................................................. 224
12.4 Emergency Response Services.................................................... 228
12.5 Credit Card Fraud....................................................................... 232
13 Conclusion........................................................................................... 239
Index ............................................................................................................. 243

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