| Infrastructure networks serve communities by providing essential goods and services, for example, transportation, power and water. Natural hazard events, such as earthquakes, can damage network elements that disrupt operations on the network, leading to potentially significant economic and social losses. Simultaneous and instantaneous restoration of all damaged network elements is an ideal restoration action following the occurrence of a hazard event; however, the scale of the disruption and limitations on available physical and financial resources preclude this restoration solution. Instead, restoration actions must be prioritized preferably in a way that accounts for broader considerations, such as indirect economic losses and social impacts. Although optimal restoration design of disrupted infrastructure networks has been studied in the past, these studies focused solely on recovering the physical infrastructure as rapidly as possible within the financial constraints. In this research, the restoration problem is formulated in such a way that broader considerations such as indirect economic losses and social impacts can be factored into the decision-making.;The restoration problem is solved through a framework that is adopted from "Design by shopping" paradigm where simulation, many-objective, that is, four or more objectives, optimization and data visualization are combined. In order to expedite decision-making, a data visualization technique that reduce the cognitive efforts required to explore the solution set of a many-objective optimization problem is developed. The novel data visualization technique enables efficient exploration of the solution set by quickly revealing those objectives that have significant tradeoffs for further exploration, thus reducing the number of 2D representations that must be generated and interpreted while allowing preferences to be applied when selecting a solution. The utility of the framework for restoration design is demonstrated through two case study transportation network applications. The results of the case studies demonstrated that a clear tradeoff exists between the restoration costs and the indirect economic and social losses and that a marginal increase in restoration costs with a different allocation of resources could yield significant gains in indirect economic and social losses. |
