Оглавление
Jean-Paul Bourrieres. From Logistic Networks to Social Networks
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
From Logistic Networks to Social Networks. Similarities, Specificities, Modeling, Evaluation
Foreword
Introduction
1. Network Typology. 1.1. Introduction
1.1.1. Network description levels
1.1.2. Network, graph and flow
1.1.3. Shared or dedicated infrastructure
1.1.4. User inclusion
1.2. The principal networks
1.2.1. (Human) transport networks
1.2.2. (Goods) distribution and collection networks
1.2.3. Dedicated distribution and collection networks (of fluids and energy)
1.2.4. IT networks
1.2.5. Communication networks
1.2.6. Social and digital social networks
1.3. Characterization and typology of networks
1.3.1. Key characteristics
1.3.2. Network integration
1.3.3. Typology
1.4. Engineering issues
1.5. Performance indicators, evaluation, optimization
1.5.1. Performance indicators
1.5.2. Evaluation and optimization
1.6. Conclusion
2. Modeling Discrete Flow Networks. 2.1. Introduction
2.2. Structure
2.3. Characterization of a discrete flow
2.3.1. Statistical description
2.3.2. Probabilistic description
2.4. Activities
2.5. Control system
2.6. Resources
2.7. Fluid kinematics
2.7.1. Flow/resource/decision synchronization
2.7.2. Congestion phenomenon
2.7.3. Dissemination of information in social networks
2.8. Formalisms for modeling flows in a network
2.8.1. BPM tools
2.8.2. Timed Petri nets
2.8.3. Flow networks
2.8.4. Queuing networks
2.9. Multi-modeling
2.9.1. Multi-formalism versus mono-formalism
2.9.2. The DEVS hierarchical model
2.9.3. Multi-layer networks
2.10. Conclusion
3. Exact Methods Applied to the Flow Analysis of Topological Networks. 3.1. Introduction
3.2. Additive flow networks – deterministic modeling by flow networks
3.2.1. Two-terminal series–parallel graph
3.2.2. General case – max-flow/min-cut
3.3. Additive flow networks – stochastic modeling by queuing networks
3.4. Synchronized flow networks – modeling by timed event graphs
3.4.1. Steady-state analysis of timed event graphs
3.4.2. Example of application: sizing a flow-shop
3.5. Conclusion
4. Simulation Techniques Applied to the Analysis of Sociological Networks. 4.1. Introduction
4.2. Simulation techniques
4.2.1. Discrete event simulation (worldviews)
4.2.2. DEVS formalism
4.2.3. Coupling simulation/resolutive methods
4.2.4. Distributed simulation
4.2.5. Architectural solutions
4.2.6. Time management and synchronization
4.2.7. Pessimistic approach
4.2.8. Optimistic approach
4.2.9. HLA
4.2.10. Cosimulation
4.2.11. FMI/FMU
4.2.12. FMI/FMU and HLA coupling
4.3. Simulation of flows in sociological networks
4.3.1. Behavioral simulation based on DEVS formalism
4.3.2. Application study
4.4. Conclusion
5. Smart Grid
5.1. Summary of the study
5.2. Demand profile
5.3. Solar power station, fuel station and regional import
5.4. Hydroelectric power station and PHES
5.5. Operational issues
5.6. Model. 5.6.1. Decision variables
5.6.2. Constraints
5.6.3. Objective function
5.7. Optimization results
6. Forestry Logistics
6.1. Summary of the study
6.2. Forest timber supply problem
6.3. Tactical planning model
6.4. Logistics benchmarking
6.4.1. AS IS scenario (non-collaborative logistics)
6.4.2. TO BE scenario (collaborative logistics)
6.4.3. Results
6.5. Conclusion
7. Multi-layered Digital Social Networks
7.1. Summary of the study
7.2. Digital social networks
7.3. Studying digital social networks via an interview broadcast
7.3.1. Pre-interview social network scenario
7.3.2. Social network audience
7.4. Modeling and simulation
7.4.1. Modeling the interview production and broadcast processes
7.4.2. MSN/HLA simulation architecture
7.5. Simulation results
7.6. Conclusion and perspectives
References
Index. A, B, C
D, E
F, G, H
I, L, M, N
O, P, Q
R, S
T, U
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