Quantifying restoration costs in the aftermath of an extreme event using system dynamics and dynamic mathematical modeling approaches

Extreme events such as earthquakes, hurricanes, and the like, lead to devastating effects that may render multiple supply chain critical infrastructure elements inoperable. The economic losses caused by extreme events continue well after the emergency response phase has ended and are a key factor in determining the best path for post-disaster restoration. It is essential to develop efficient restoration and disaster management strategies to ameliorate the losses from such events. This dissertation extends the existing knowledge base on disaster management and restoration through the creation of models and tools that identify the relationship between production losses and restoration costs. The first research contribution is a system dynamics inoperability model that determines inputs, outputs, and flows for roadway networks. This model can be used to identify the connectivity of road segments and better understand how inoperability contributes to economic consequences. The second contribution is an algorithm that integrates critical infrastructure data derived from bottom-up cost estimation technique as part of an object-oriented software tool that can be used to determine the impact of system disruptions. The third contribution is a dynamic mathematical model that establishes a framework to estimate post-disaster restoration costs from a whole system perspective. Engineering managers, city planners, and policy makers can use the methodologies developed in this research to develop effective disaster planning schemas and to prioritize post-disaster restoration operations --Abstract, page iv

Interdependent Scheduling Games

We propose a model of interdependent scheduling games in which each player controls a set of services that they schedule independently. A player is free to schedule his own services at any time; however, each of these services only begins to accrue reward for the player when all predecessor services, which may or may not be controlled by the same player, have been activated. This model, where players have interdependent services, is motivated by the problems faced in planning and coordinating large-scale infrastructures, e.g., restoring electricity and gas to residents after a natural disaster or providing medical care in a crisis when different agencies are responsible for the delivery of staff, equipment, and medicine. We undertake a game-theoretic analysis of this setting and in particular consider the issues of welfare maximization, computing best responses, Nash dynamics, and existence and computation of Nash equilibria.Comment: Accepted to IJCAI 201

Bargaining Mechanisms for One-Way Games

We introduce one-way games, a framework motivated by applications in large-scale power restoration, humanitarian logistics, and integrated supply-chains. The distinguishable feature of the games is that the payoff of some player is determined only by her own strategy and does not depend on actions taken by other players. We show that the equilibrium outcome in one-way games without payments and the social cost of any ex-post efficient mechanism, can be far from the optimum. We also show that it is impossible to design a Bayes-Nash incentive-compatible mechanism for one-way games that is budget-balanced, individually rational, and efficient. To address this negative result, we propose a privacy-preserving mechanism that is incentive-compatible and budget-balanced, satisfies ex-post individual rationality conditions, and produces an outcome which is more efficient than the equilibrium without payments. The mechanism is based on a single-offer bargaining and we show that a randomized multi-offer extension brings no additional benefit.Comment: An earlier, shorter version of this paper appeared in Proceedings of the Twenty-Fourth International joint conference on Artificial Intelligence (IJCAI) 201

Classifying Interdependencies in the Food and Agriculture Critical Infrastructure Sector

This work classifies examples of infrastructure interdependencies found in the food and agriculture critical infrastructure sector. Interdependencies are identified through an examination of rice and poultry agriculture throughout the state of Arkansas. The subtleties of interdependence examples in the food and agriculture sector are inadequately captured by the well-studied interdependence classification taxonomies. Through 39 interviews, we develop an understanding of the subtle temporal, geographic, and productivity scales of interdependence in over 100 examples and present five new, distinct classifications of interdependence: (1) dynamic physical, (2) dynamic geographic, (3) deadline, (4) delay, and (5) human, economic, and natural resource interdependencies. An analysis of these inter- dependencies and their intricacies provides the opportunity to generalize these ideas across other critical infrastructure sectors and model infrastructure restoration and resilience with greater concern for seasonality, resource scarcity, and punctuality

Resilience-Driven Post-Disruption Restoration of Interdependent Critical Infrastructure Systems Under Uncertainty: Modeling, Risk-Averse Optimization, and Solution Approaches

Critical infrastructure networks (CINs) are the backbone of modern societies, which depend on their continuous and proper functioning. Such infrastructure networks are subjected to different types of inevitable disruptive events which could affect their performance unpredictably and have direct socioeconomic consequences. Therefore, planning for disruptions to CINs has recently shifted from emphasizing pre-disruption phases of prevention and protection to post-disruption studies investigating the ability of critical infrastructures (CIs) to withstand disruptions and recover timely from them. However, post-disruption restoration planning often faces uncertainties associated with the required repair tasks and the accessibility of the underlying transportation network. Such challenges are often overlooked in the CIs resilience literature. Furthermore, CIs are not isolated from each other, but instead, most of them rely on one another for their proper functioning. Hence, the occurrence of a disruption in one CIN could affect other dependent CINs, leading to a more significant adverse impact on communities. Therefore, interdependencies among CINs increase the complexity associated with recovery planning after a disruptive event, making it a more challenging task for decision makers. Recognizing the inevitability of large-scale disruptions to CIs and their impacts on societies, the research objective of this work is to study the recovery of CINs following a disruptive event. Accordingly, the main contributions of the following two research components are to develop: (i) resilience-based post-disruption stochastic restoration optimization models that respect the spatial nature of CIs, (ii) a general framework for scenario-based stochastic models covering scenario generation, selection, and reduction for resilience applications, (iii) stochastic risk-related cost-based restoration modeling approaches to minimize restoration costs of a system of interdependent critical infrastructure networks (ICINs), (iv) flexible restoration strategies of ICINs under uncertainty, and (v) effective solution approaches to the proposed optimization models. The first research component considers developing two-stage risk-related stochastic programming models to schedule repair activities for a disrupted CIN to maximize the system resilience. The stochastic models are developed using a scenario-based optimization technique accounting for the uncertainties of the repair time and travel time spent on the underlying transportation network. To assess the risks associated with post-disruption scheduling plans, a conditional value-at-risk metric is incorporated into the optimization models through the scenario reduction algorithm. The proposed restoration framework is illustrated using the French RTE electric power network. The second research component studies the restoration problem for a system of ICINs following a disruptive event under uncertainty. A two-stage mean-risk stochastic restoration model is proposed to minimize the total cost associated with ICINs unsatisfied demands, repair tasks, and flow. The model assigns and schedules repair tasks to network-specific work crews with consideration of limited time and resources availability. Additionally, the model features flexible restoration strategies including a multicrew assignment for a single component and a multimodal repair setting along with the consideration of full and partial functioning and dependencies between the multi-network components. The proposed model is illustrated using the power and water networks in Shelby County, Tennessee, United States, under two hypothetical earthquakes. Finally, some other topics are discussed for possible future work

Drinking-Water and drinking water: Trajectories of Provision and Consumption in the UK, Taiwan and Delhi

In many advanced economies, water is one of the most taken-for-granted and ?ordinary? objects of consumption. However, the emergence of all-purpose (including drinking) water was the outcome of long and varied historical processes, involving major changes in both systems of provision and patterns of consumption. In many parts of the world, there are still different types and sources of water for different consumption purposes, and there are significant inequalities in rights over this most basic resource, especially water fit for drinking. Water presents a critical lens to explore organisations of economies of a good, which are often a complex mix of private, commercial, or public systems of provision. This paper will argue that an ?instituted economic process? approach is fruitful in exploring diverse configurations of production, appropriation, distribution and consumption of water. In particular, it will argue that practices of consumption are best analysed as integral and necessary dimensions of these wider configurations of economic organisation. The analysis will draw on my current comparative research in the UK, Delhi and Taiwan, and empirically demonstrates the need to problematise water as a consumption good, in order to understand its rich and complex diversity. This research arose from my comparative research on bottled water, undertaken in the wider research programme of the ESRC Sustainable Practices Research Group

A Parallel Fast-Track Service Restoration Strategy Relying on Sectionalized Interdependent Power-Gas Distribution Systems

In the distribution networks, catastrophic events especially those caused by natural disasters can result in extensive damage that ordinarily needs a wide range of components to be repaired for keeping the lights on. Since the recovery of system is not technically feasible before making compulsory repairs, the predictive scheduling of available repair crews and black start resources not only minimizes the customer downtime but also speeds up the restoration process. To do so, this paper proposes a novel three-stage buildup restoration planning strategy to combine and coordinate repair crew dispatch problem for the interdependent power and natural gas systems with the primary objective of resiliency enhancement. In the proposed model, the system is sectionalized into autonomous subsystems (i.e., microgrid) with multiple energy resources, and then concurrently restored in parallel considering cold load pick-up conditions. Besides, topology refurbishment and intentional microgrid islanding along with energy storages are applied as remedial actions to further improve the resilience of interdependent systems while unpredicted uncertainties are addressed through stochastic/IGDT method. The theoretical and practical implications of the proposed framework push the research frontier of distribution restoration schemes, while its flexibility and generality support application to various extreme weather incidents.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Enhancing the resilience of social infrastructures: issues on agents, artefacts and processes. Proceedings of the 2016 Modena Workshop

In the social sciences domain, the term 'resilience' is usually associated to a wide set of changes that affect people and their communities. In particular, both the Hyogo Framework for Action 2005–2015 and the Sendai Framework explicitly focus on the way in which communities face both natural and man-made hazards. To this respect, both material and non-material infrastructures play a critical role, hence deserving a specific focus when assessing local communities' level of resilience. Among them, this paper focuses on: health services, social services, government (according to a multi-level perspective, from the national to the local level), communication infrastructure (i.e. specific tools to interconnect all aforementioned networks). Firstly, this paper discusses some of the most important issues and theoretical frameworks that should be addressed in the analysis of the processes of enhancing the resilience of social infrastructures. Secondly, the discussion that took place in a workshop promoted in May 2016 as the outcome of a one-year dialogue across a group of EU researchers is returned. The debate moves from some theoretical perspectives on resilience and it eventually returns some case studies and real experiences, such as the actions of local governments and the role of risk communication