Solving Markov decision processes for network-level post-hazard recovery via simulation optimization and rollout

Computation of optimal recovery decisions for community resilience assurance post-hazard is a combinatorial decision-making problem under uncertainty. It involves solving a large-scale optimization problem, which is significantly aggravated by the introduction of uncertainty. In this paper, we draw upon established tools from multiple research communities to provide an effective solution to this challenging problem. We provide a stochastic model of damage to the water network (WN) within a testbed community following a severe earthquake and compute near-optimal recovery actions for restoration of the water network. We formulate this stochastic decision-making problem as a Markov Decision Process (MDP), and solve it using a popular class of heuristic algorithms known as rollout. A simulation-based representation of MDPs is utilized in conjunction with rollout and the Optimal Computing Budget Allocation (OCBA) algorithm to address the resulting stochastic simulation optimization problem. Our method employs non-myopic planning with efficient use of simulation budget. We show, through simulation results, that rollout fused with OCBA performs competitively with respect to rollout with total equal allocation (TEA) at a meagre simulation budget of 5-10% of rollout with TEA, which is a crucial step towards addressing large-scale community recovery problems following natural disasters.Comment: Submitted to Simulation Optimization for Cyber Physical Energy Systems (Special Session) in 14th IEEE International Conference on Automation Science and Engineerin

Resilience-based decision framework to determine performance targets for the built environment, A

2018 Spring.Includes bibliographical references.Current design codes and standards focus on the design of individual facilities. A typical building is designed with the objective of the life safety of occupants. Even performance-based design approaches assess the required physical performance of an individual structure in order to satisfy prescribed criteria for that structure individually. Thus, even these performance objectives are likely not sufficient for a broad view of community-resilience goals. A modern community is made up of highly coupled networks, and disruptions within one or more networks may lead to disruptions to other networks. If a large number of buildings within a community become non-functional for a long time following an event, either because of physical damage or loss of utilities such as electric power and/or water, the consequences may affect other parts of the community such that, eventually, significant socioeconomic losses occur. Therefore, the current approach for designing individual physical components within a community can be reimagined such that it not only takes into account the performance of a component individually after a catastrophic event but also considers the consequences its design has on a community. The main purpose of this dissertation is to develop a methodology that links the performance of components within the built environment to community-level resilience goals by considering the dependencies and cross-dependencies between components and networks. Therefore, ultimately, this methodology enables disaggregation of the community-level objectives into a set of performance targets for the components of the built environment, which leads itself to the needs of policymakers and community leaders in order to make long-term planning decisions for a community

Functionality, Access, and Implications: Assessing the Role of Organizations in Community Disaster Resilience

Communities are complex systems defined by the interaction of social, economic, environmental, and physical systems. Increasing rates and intensities of climatic natural hazards, coupled with rising urbanization and an increase in quality-of-life dependency on social and economic systems, underlines the importance of improving the resilience of buildings and infrastructure systems that play a key role in ensuring the functionality of the community's social and economic systems. Building codes are principal regulatory documents that aid in achieving this goal. However, building codes historically set their design-level performance goal with a primary focus on avoiding loss of life with limited considerations on how a building is actually used by its occupants or the broader community. To move towards resilience, the next generation of building codes should modify their design philosophy and extend their design goals to incorporate functionality-related performance goals into the design process, where functionality goals must include social, economic, and physical aspects of buildings and infrastructure.This study posits that organizations are the key lynchpin connecting buildings and infrastructure systems to social and economic systems. Utilizing the Community Capitals framework, we propose a novel framework for assessing the implications of disruptions in the accessibility and functionality of organizations contributing to the resilience of a community’s social and economic systems. The framework exemplifies the deliberate incorporation of organization-level functionality into community resilience and bridges the gap between the community’s social and economic characteristics with conventional engineering-focused community resilience frameworks through including the concept of accessibility. To identify components contributing to the functionality of an organization and define organizational functionality states, fault tree models were employed. In addition to conventional physical components and utilities, staff and supply chain are introduced as critical non-physical components contributing to the availability, acceptability, and adequacy of products offered by organizations. Defining accessibility as the use of available products by community members with reasonable effort and cost to meet an essential need, two novel metrics for measuring accessibility are developed. The metrics consider access from the perspective of both service users and providers and reconcile accessibility with organizational functionality by incorporating proximity, availability, acceptability, and adequacy dimensions in measuring accessibility to both tangible products and intangible services. To demonstrate the application of the framework the research used the Lumberton virtual community resilience testbed. Virtual testbeds are an effective tool to test, verify, and validate community resilience models and advance the state of knowledge on community resilience. The application of virtual testbeds is increasing as quantitative hazard research aims to move from component- and building-level modeling into the interdisciplinary space of community-level modeling for resilience. However, the characteristic of testbeds, their components, and development procedures was something embedded in published works, and somewhat ambiguous. Thus, we leveraged the current momentum on using virtual testbeds for community resilience analysis and performed a systematic literature review and an expert survey to dissect what testbeds are in practice. We, finally, defined testbeds as a virtual environment with enough supporting architecture and metadata to be representative of one or more systems such that the testbed can be used to (a) design experiments, (b) examine model or system integration, and (c) test theories. From the literature review, it was illuminated that the lack of a standardized and systematic approach for testbed development, testbed publication, or testbed reuse virtual testbeds is a significant issue that needs to be addressed. Thus, a systematic schema for testbed development is also proposed. The workflow facilitates testbed creations by introducing a generic structure defining minimum requirements for initiating a testbed and by defining a step-by-step development procedure. The application of the proposed workflow has been demonstrated by establishing a testbed based on Onslow County, NC using publicly available data in the United States. The testbed is shared using the DesignSafe-CI for reusing by other researchers. The other significant challenge in developing virtual community resilience testbeds is incorporating social systems and phenomena into testbeds. Social vulnerability indices are a convenient way to account for differential experiences and starting conditions of the population in resilience assessments. This dissertation proposes a scalable index, termed Social Vulnerability Score (SVS), to serve the purpose of testbed development. The SVS overcomes two important limitations of existing indices: it is constructed using an approach that does not decrease in validity with changing spatial resolution, and it only needs to be calculated for the geographic area of interest, instead of for the entire county thereby significantly reducing computational effort for testbed developers and users. The proposed SVS aggregates the ratio of a set of demographics from U.S. Census datasets at the desired location against their national average values. The resulting scores are mapped into five levels, called zones, ranging from very low vulnerability (zone 1) to very high (zone 5). The SVS model is incorporated into the Interdependent Networked Community Resilience Modeling Environment (IN-CORE). Lastly, to exemplify the application of social vulnerability in the proposed framework, inequities in accessibility to schools after 2016 Hurricane Matthew were assessed across the different socially vulnerable populations in the Lumberton Testbed