Robustness and Resilience

Klau, Gunnar W.; Weiskircher, René

doi:10.1007/978-3-540-31955-9_15

Cited by 38 publications

(18 citation statements)

References 18 publications

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“…Although top-down control of this order is absent, it is adaptive in the sense that individual and collective behavior can mutate and self-organize in order to create a system that can be more robust [255] and resilient [256] than comparable systems with top-down control. The Internet is a good example [257].…”

Section: From Dynamic To Complex Adaptive Systemsmentioning

confidence: 99%

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Hoekstra

Steinbuch

Verbong³

2017

Complexity

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The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. We review the literature regarding agent-based economics, disruptive innovation, and transition management and determine the following requirements. Actors must be detailed, heterogeneous, interacting, learning, and strategizing. Technology should be represented as a detailed and heterogeneous portfolio that can develop in a bottom-up manner, using endogenous feedback loops. Assumptions about discount rates and the social cost of carbon should be configurable. The model should contain interactions between the global, national, local, and individual level. A review of modelling techniques shows that equilibrium models are unsuitable and that system dynamics and discrete event simulation are too limited. The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled. But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within the agent-based framework. We conclude with practical guidelines.

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Section: From Dynamic To Complex Adaptive Systemsmentioning

confidence: 99%

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Hoekstra

Steinbuch

Verbong³

2017

Complexity

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“…Such events may seriously disrupt or delay the flow of people, goods, information and funds, and thus lead to higher costs or reduced sales [5]. A supply network's resilience against disruptions lies in its ability to maintain operations and connectedness under the loss of some structures or functions [6]. Therefore, building resilient supply networks has high priority, and it has attracted the attention of managers, shareholders, and researchers [7].…”

mentioning

confidence: 99%

Analyzing the Resilience of Complex Supply Network Topologies Against Random and Targeted Disruptions

Zhao

Kumar

Harrison

et al. 2011

IEEE Systems Journal

236

158

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Abstract-In this paper, we study the resilience of supply networks against disruptions and provide insights to supply chain managers on how to construct a resilient supply network from the perspective of complex network topologies. Our goal is to study how different network topologies, which are created from different growth models, affect the network's resilience against both random and targeted disruptions. Of particular interest are situations where the type of disruption is unknown. Using a military logistic network as a case study, we propose new network resilience metrics that reflect the heterogeneous roles (e.g., supply, relay, and demand) of nodes in supply networks. We also present a hybrid and tunable network growth model called Degree and Locality-based Attachment (DLA), in which new nodes make connections based on both degree and locality. Using computer simulations, we compare the resilience of several supply network topologies that are generated with different growth models. The results show that the new resilience metrics can capture important resilience requirements for supply networks very well. We also found that the supply network topology generated by the DLA model provides balanced resilience against both random and targeted disruptions.

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“…Intuitively, we may think of a graph as being better connected when it takes the removal of many elements to break it into smaller components. Such graphs are also said to be ‘robust’, an expression which highlights the fact that the potential for communication among elements in such networks is resistant to disruption via the failure of individual network elements (see Klau & Weiskircher, 2005 for an in‐depth review). The extent to which a graph exhibits such robustness may be measured by the sizes of its minimum edge or vertex cut (i.e.…”

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confidence: 99%

Social network analysis: A methodological introduction

Butts

2008

Asian J of Social Psycho

416

281

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Social network analysis is a large and growing body of research on the measurement and analysis of relational structure. Here, we review the fundamental concepts of network analysis, as well as a range of methods currently used in the field. Issues pertaining to data collection, analysis of single networks, network comparison, and analysis of individual-level covariates are discussed, and a number of suggestions are made for avoiding common pitfalls in the application of network methods to substantive questions.

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Robustness and Resilience

Cited by 38 publications

References 18 publications

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Analyzing the Resilience of Complex Supply Network Topologies Against Random and Targeted Disruptions

Social network analysis: A methodological introduction

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