Table of Contents
Acknowledgements xi
1 Introduction 1
1.1 Problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Definitions and scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.1 Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.2 Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.3 Model and simulation . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.4 Actor and agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.5 Socio-technical systems . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 Examples of new challenges . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3.1 Vertical unbundling of the energy sector . . . . . . . . . . . . . . 6
1.3.2 High speed rail . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.3.3 Carbon capture and storage . . . . . . . . . . . . . . . . . . . . . 7
1.3.4 Commonalities and decision support for socio-technical systems . 8
1.4 Research objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.5 Audience and relevance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.5.1 Audience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.5.2 Scientific relevance . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.5.3 Societal relevance . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.6 Research questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.7 Overview of this thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.7.1 Thesis outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.7.2 Reader guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2 Modelling socio-technical systems 17
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2 Modelling socio-technical systems . . . . . . . . . . . . . . . . . . . . . . 17
2.2.1 Research groups and application domains . . . . . . . . . . . . . . 18
2.2.2 Modelling approaches for socio-technical systems . . . . . . . . . . 20
2.2.3 In-depth study of potentially interesting modelling approaches . . 22
2.2.4 Conclusions part 1 . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.3 Agent-based modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.3.1 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.3.2 Interpretations of the concept “agent” . . . . . . . . . . . . . . . . 31
2.3.3 Modelling paradigm spectrum . . . . . . . . . . . . . . . . . . . . 31
2.4 Agent-based modelling of socio-technical systems . . . . . . . . . . . . . . 34
2.4.1 Agent-based model for energy systems analysis . . . . . . . . . . . 34
2.4.2 Multi-agent model predictive control . . . . . . . . . . . . . . . . 36
2.4.3 Controlling electricity failures with cooperative agents . . . . . . . 37
2.4.4 Agent-based modelling of transport and energy systems . . . . . . 38
2.4.5 BRIDGE agent architecture . . . . . . . . . . . . . . . . . . . . . . 39
2.4.6 Modelling the evolution of large-scale socio-technical systems . . . 39
2.4.7 Conclusions on keywords . . . . . . . . . . . . . . . . . . . . . . 40
2.4.8 Agent-based approaches in the energy domain . . . . . . . . . . . 40
2.4.9 Conclusions part 2 . . . . . . . . . . . . . . . . . . . . . . . . . . 42
2.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
2.6 Research questions revisited . . . . . . . . . . . . . . . . . . . . . . . . . 44
3 Framework 45
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.2 Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.3 Ontologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3.1 What is an ontology? . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.3.2 An example: the girl with a pearl earring . . . . . . . . . . . . . . 48
3.3.3 Why use an ontology? . . . . . . . . . . . . . . . . . . . . . . . . 49
3.3.4 System decomposition method . . . . . . . . . . . . . . . . . . . 50
3.3.5 Software tools for ontology development . . . . . . . . . . . . . . 50
3.4 Approach to the development of a framework . . . . . . . . . . . . . . . 51
3.4.1 Initial state . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.4.2 Iterations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.4.3 Stop condition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.5 Ontology of socio-technical systems . . . . . . . . . . . . . . . . . . . . . 57
3.5.1 Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.5.2 Edges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.5.3 Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.5.4 Instances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
3.5.5 Putting it all together . . . . . . . . . . . . . . . . . . . . . . . . . 71
3.6 Modelling steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.7 Core elements and conclusions . . . . . . . . . . . . . . . . . . . . . . . . 74
4 Case studies — application and use of the framework 75
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.2 Case 1: Intermodal freight hub . . . . . . . . . . . . . . . . . . . . . . . . 76
4.2.1 Conceptualisation in terms of actors and physical systems . . . . . 77
4.2.2 Definition of possible disturbances on the system . . . . . . . . . 78
4.2.3 Refinement of the generic ontology with new abstract classes . . . 79
4.2.4 Creation of concrete instances . . . . . . . . . . . . . . . . . . . . 80
4.2.5 Implementation of the behaviour of the agents . . . . . . . . . . . 80
4.2.6 Verification and validation of the model . . . . . . . . . . . . . . . 81
4.2.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.3 Case 2: Oil refinery supply chain . . . . . . . . . . . . . . . . . . . . . . 81
4.3.1 Conceptualisation in terms of actors and physical systems . . . . . 81
4.3.2 Definition of possible disturbances on the system . . . . . . . . . 83
4.3.3 Refinement of the generic ontology with new abstract classes . . . 84
4.3.4 Creation of concrete instances . . . . . . . . . . . . . . . . . . . . 84
4.3.5 Implementation of the behaviour of the agents . . . . . . . . . . . 84
4.3.6 Verification and validation of the model . . . . . . . . . . . . . . . 86
4.3.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4.4 Case 3: Chocolate game . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
4.4.1 Conceptualisation in terms of actors and physical systems . . . . . 87
4.4.2 Definition of possible disturbances on the system . . . . . . . . . 87
4.4.3 Refinement of the generic ontology with new abstract classes . . . 88
4.4.4 Creation of concrete instances . . . . . . . . . . . . . . . . . . . . 88
4.4.5 Implementation of the behaviour of the agents . . . . . . . . . . . 88
4.4.6 Verification and validation of the model . . . . . . . . . . . . . . . 89
4.4.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
4.5 Cases by others . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.5.1 Case 4: Evolution of industrial clusters . . . . . . . . . . . . . . . 92
4.5.2 Case 5: CO2 emission trading . . . . . . . . . . . . . . . . . . . . 94
4.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5 Framework development trajectory 99
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
5.2 Analysis tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.2.1 Design of the tool . . . . . . . . . . . . . . . . . . . . . . . . . . 101
5.2.2 Data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
5.2.3 Missing values . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
5.2.4 Lessons learnt on the analysis tool . . . . . . . . . . . . . . . . . . 103
5.3 Ontology development . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.3.1 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.3.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.4 Re-use of concepts in practice . . . . . . . . . . . . . . . . . . . . . . . . 105
5.4.1 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
5.4.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
5.5 Re-use of instances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
5.5.1 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
5.5.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
6 Benchmarking 113
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
6.2 Benchmarking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
6.2.1 Definition of the objectives for the study . . . . . . . . . . . . . . 115
6.2.2 Identification of what is to be benchmarked . . . . . . . . . . . . . 115
6.2.3 Evaluation if objects of study are comparable . . . . . . . . . . . . 115
6.2.4 Determination and specification of performance measures . . . . . 117
6.2.5 Description of scenarios and simulation . . . . . . . . . . . . . . . 118
6.3 Models of the oil refinery supply chain . . . . . . . . . . . . . . . . . . . 119
6.3.1 Model E: An equation-based model in Excel . . . . . . . . . . . . 119
6.3.2 Model M: A numerical model in MATLAB . . . . . . . . . . . . . . 121
6.3.3 Model R: An agent-based model in Repast . . . . . . . . . . . . . 122
6.3.4 Mapping the models on the model-space . . . . . . . . . . . . . . 123
6.4 Benchmarking case study: Oil refinery supply chain . . . . . . . . . . . . 123
6.4.1 Definition of the objectives for the study . . . . . . . . . . . . . . 123
6.4.2 Identification of what is to be benchmarked . . . . . . . . . . . . . 123
6.4.3 Evaluation if objects of study are comparable . . . . . . . . . . . . 124
6.4.4 Determination and specification of performance measures . . . . . 129
6.4.5 Description of scenarios and simulation . . . . . . . . . . . . . . . 129
6.4.6 Benchmarking conclusions . . . . . . . . . . . . . . . . . . . . . . 130
6.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
7 Decision support with agent-based models 137
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
7.1.1 Formulate the decision problem . . . . . . . . . . . . . . . . . . . 138
7.1.2 Select the decision problem solving method . . . . . . . . . . . . . 139
7.1.3 Perform experiments . . . . . . . . . . . . . . . . . . . . . . . . . 140
7.1.4 Analyse the results . . . . . . . . . . . . . . . . . . . . . . . . . . 140
7.2 Decision support for the location of an intermodal freight hub . . . . . . 141
7.2.1 Formulate the decision problem . . . . . . . . . . . . . . . . . . . 142
7.2.2 Select the decision problem solving method . . . . . . . . . . . . . 143
7.2.3 Perform experiments . . . . . . . . . . . . . . . . . . . . . . . . . 143
7.2.4 Analyse the results . . . . . . . . . . . . . . . . . . . . . . . . . . 144
7.2.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
7.3 Decision support for abnormal situation management in a refinery . . . . 146
7.3.1 Formulate the decision problem . . . . . . . . . . . . . . . . . . . 146
7.3.2 Select the decision problem solving method . . . . . . . . . . . . . 148
7.3.3 Perform experiments . . . . . . . . . . . . . . . . . . . . . . . . . 149
7.3.4 Analyse the results . . . . . . . . . . . . . . . . . . . . . . . . . . 149
7.3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
7.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
8 Conclusions, discussion and future research 153
8.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
8.1.1 Modelling framework for socio-technical systems . . . . . . . . . . 154
8.1.2 Categories of modelling paradigms . . . . . . . . . . . . . . . . . 155
8.1.3 Benchmarking modelling paradigms . . . . . . . . . . . . . . . . . 155
8.1.4 Advantages of agent-based modelling . . . . . . . . . . . . . . . . 155
8.1.5 Ontology development . . . . . . . . . . . . . . . . . . . . . . . . 156
8.1.6 Decision support . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
8.2 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
8.2.1 The best approach? . . . . . . . . . . . . . . . . . . . . . . . . . . 156
8.2.2 Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
8.2.3 Benchmarking . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
8.2.4 Ontology languages . . . . . . . . . . . . . . . . . . . . . . . . . 157
8.2.5 Distributed controllers . . . . . . . . . . . . . . . . . . . . . . . . 158
8.2.6 Application in the industry . . . . . . . . . . . . . . . . . . . . . 158
8.3 Recommendations for future research . . . . . . . . . . . . . . . . . . . . 159
8.4 Final remark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
Appendices 161
A Literature study on socio-technical modelling 163
A.1 Literature study approach . . . . . . . . . . . . . . . . . . . . . . . . . . 163
A.2 Application domains and background of authors . . . . . . . . . . . . . . 163
A.2.1 Completeness of study . . . . . . . . . . . . . . . . . . . . . . . . 166
A.3 Modelling approaches for socio-technical systems . . . . . . . . . . . . . . 166
A.3.1 Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
A.3.2 Selection of papers . . . . . . . . . . . . . . . . . . . . . . . . . . 168
A.4 Agent-based modelling in the energy domain . . . . . . . . . . . . . . . . 169
A.4.1 Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
B Survey on agent-based systems 173
B.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
B.2 Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
B.3 List of answers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
B.4 List of participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
C Models built with the framework 181
C.1 Brief description of models . . . . . . . . . . . . . . . . . . . . . . . . . . 181
C.2 Time planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
D Classes added to the ontology 185
D.1 List of classes added . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
Bibliography 188
Glossary 209
Summary 211
Samenvatting 217
Curriculum vitae 223
List of publications 225
NGInfra PhD thesis series on infrastructures 229
Abstract
What is a suitable modelling approach for socio-technical systems? The answer to this question is of great importance to decision makers in large scale interconnected network systems. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level jungle. Models to support such an actor should be able to capture both the physical and social reality of the system, their interactions with one another and the external dynamic environment. Moreover, they must allow users to experiment with changes in both the physical and the social network configuration. To deal with these challenges a generic agent-based modelling framework for socio-technical systems is developed in this thesis. The cornerstone of the framework is a shared language formalised in an ontology, which forms the interface needed to bring different elements of the system (both social and physical) together, to interconnect different models and ensure interoperability. The re-usability of building blocks helps modellers build new models more efficiently. The models developed with the new framework are shown to offer valuable decision support in case studies of an oil refinery supply chain and an intermodal freight hub.
