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From Logistic Networks to Social Networks


From Logistic Networks to Social Networks

Similarities, Specificities, Modeling, Evaluation
1. Aufl.

von: Jean-Paul Bourrieres, Nathalie Pinede, Mamadou Kaba Traore, Gregory Zacharewicz

126,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 10.06.2022
ISBN/EAN: 9781119988694
Sprache: englisch
Anzahl Seiten: 208

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Beschreibungen

As a result of its widespread implementation in economic and social structures, the network concept appears to be a paradigm of the contemporary world. The need for various services – transport, energy, consumption of manufacturing goods, provision of care, information and communication, etc. – draws users into interwoven networks which are meshes of material and immaterial flows. In this context, the user is a consumer of goods and services from industries and administrations, or they themselves are part of the organization (digital social networks).<br /><br />This book examines the invariants that unify networks in their diversity, as well as the specificities that differentiate them. It provides a reading grid that distinguishes a generic level where these systems find a common interpretation, and a specific level where appropriate analytical methods are used. Three case studies from different fields are presented to illustrate the purpose of the book in detail.
<p>Foreword ix</p> <p>Introduction xi</p> <p><b>Part 1. Network Variety and Modeling 1</b></p> <p><b>Chapter 1. Network Typology 3</b></p> <p>1.1. Introduction 3</p> <p>1.1.1. Network description levels 3</p> <p>1.1.2. Network, graph and flow 4</p> <p>1.1.3. Shared or dedicated infrastructure 5</p> <p>1.1.4. User inclusion 6</p> <p>1.2. The principal networks 6</p> <p>1.2.1. (Human) transport networks 6</p> <p>1.2.2. (Goods) distribution and collection networks 7</p> <p>1.2.3. Dedicated distribution and collection networks (of fluids and energy) 8</p> <p>1.2.4. IT networks 9</p> <p>1.2.5. Communication networks 9</p> <p>1.2.6. Social and digital social networks 10</p> <p>1.3. Characterization and typology of networks 11</p> <p>1.3.1. Key characteristics 11</p> <p>1.3.2. Network integration 12</p> <p>1.3.3. Typology 13</p> <p>1.4. Engineering issues 16</p> <p>1.5. Performance indicators, evaluation, optimization 18</p> <p>1.5.1. Performance indicators 18</p> <p>1.5.2. Evaluation and optimization 20</p> <p>1.6. Conclusion 23</p> <p><b>Chapter 2. Modeling Discrete Flow Networks 25</b></p> <p>2.1. Introduction 25</p> <p>2.2. Structure 28</p> <p>2.3. Characterization of a discrete flow 30</p> <p>2.3.1. Statistical description 30</p> <p>2.3.2. Probabilistic description 32</p> <p>2.4. Activities 32</p> <p>2.5. Control system 37</p> <p>2.6. Resources 40</p> <p>2.7. Fluid kinematics 41</p> <p>2.7.1. Flow/resource/decision synchronization 42</p> <p>2.7.2. Congestion phenomenon 48</p> <p>2.7.3. Dissemination of information in social networks 51</p> <p>2.8. Formalisms for modeling flows in a network 52</p> <p>2.8.1. BPM tools 53</p> <p>2.8.2. Timed Petri nets 53</p> <p>2.8.3. Flow networks 54</p> <p>2.8.4. Queuing networks 55</p> <p>2.9. Multi-modeling 57</p> <p>2.9.1. Multi-formalism versus mono-formalism 57</p> <p>2.9.2. The DEVS hierarchical model 60</p> <p>2.9.3. Multi-layer networks 62</p> <p>2.10. Conclusion 64</p> <p><b>Part 2. Network Analysis Methods and Applications 67</b></p> <p><b>Chapter 3. Exact Methods Applied to the Flow Analysis of Topological Networks 69</b></p> <p>3.1. Introduction 69</p> <p>3.2. Additive flow networks – deterministic modelling by flow networks 71</p> <p>3.2.1. Two-terminal series–parallel graph 72</p> <p>3.2.2. General case – max-flow/min-cut 74</p> <p>3.3. Additive flow networks – stochastic modelling by queuing networks 76</p> <p>3.4. Synchronized flow networks – modeling by timed event graphs 81</p> <p>3.4.1. Steady-state analysis of timed event graphs 81</p> <p>3.4.2. Example of application: sizing a flow-shop 83</p> <p>3.5. Conclusion 88</p> <p><b>Chapter 4. Simulation Techniques Applied to the Analysis of Sociological Networks 91</b></p> <p>4.1. Introduction 91</p> <p>4.2. Simulation techniques 92</p> <p>4.2.1. Discrete event simulation (worldviews) 94</p> <p>4.2.2. DEVS formalism 96</p> <p>4.2.3. Coupling simulation/resolutive methods 100</p> <p>4.2.4. Distributed simulation 102</p> <p>4.2.5. Architectural solutions 103</p> <p>4.2.6. Time management and synchronization 104</p> <p>4.2.7. Pessimistic approach 104</p> <p>4.2.8. Optimistic approach 105</p> <p>4.2.9. HLA 106</p> <p>4.2.10. Cosimulation 107</p> <p>4.2.11. FMI/FMU 108</p> <p>4.2.12. FMI/FMU and HLA coupling 109</p> <p>4.3. Simulation of flows in sociological networks 110</p> <p>4.3.1. Behavioral simulation based on DEVS formalism 111</p> <p>4.3.2. Application study 113</p> <p>4.4. Conclusion 116</p> <p><b>Part 3. Case Studies 119</b></p> <p><b>Chapter 5. Smart Grid 121</b></p> <p>5.1. Summary of the study 122</p> <p>5.2. Demand profile 122</p> <p>5.3. Solar power station, fuel station and regional import 123</p> <p>5.4. Hydroelectric power station and PHES 123</p> <p>5.5. Operational issues 124</p> <p>5.6. Model 125</p> <p>5.6.1. Decision variables 125</p> <p>5.6.2. Constraints 126</p> <p>5.6.3. Objective function 127</p> <p>5.7. Optimization results 128</p> <p><b>Chapter 6. Forestry Logistics 131</b></p> <p>6.1. Summary of the study 132</p> <p>6.2. Forest timber supply problem 132</p> <p>6.3. Tactical planning model 134</p> <p>6.4. Logistics benchmarking 136</p> <p>6.4.1. AS IS scenario (non-collaborative logistics) 136</p> <p>6.4.2. TO BE scenario (collaborative logistics) 137</p> <p>6.4.3. Results 138</p> <p>6.5. Conclusion 139</p> <p><b>Chapter 7. Multi-layered Digital Social Networks 143</b></p> <p>7.1. Summary of the study 144</p> <p>7.2. Digital social networks 144</p> <p>7.3. Studying digital social networks via an interview broadcast 145</p> <p>7.3.1. Pre-interview social network scenario 146</p> <p>7.3.2. Social network audience 148</p> <p>7.4. Modeling and simulation 148</p> <p>7.4.1. Modeling the interview production and broadcast processes 148</p> <p>7.4.2. MSN/HLA simulation architecture 149</p> <p>7.5. Simulation results 152</p> <p>7.6. Conclusion and perspectives 154</p> <p>References 157</p> <p>Index 167</p>
Jean-Paul Bourrières is Emeritus Professor at the University of Bordeaux, France. <br />Nathalie Pinède is Associate Professor at Bordeaux Montaigne University, France. <br />Mamadou Kaba Traoré is Professor at the University of Bordeaux, France. <br />Gregory Zacharewicz is Professor at IMT Mines Alès, France.

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