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http://www.trb.org/AnnualMeeting/AnnualMeeting.aspx

Capacity-flow Feature-based Restoration Strategy Optimization for Resilient Transportation Systems to Enhance Mobility, Accessibility, and Equity after Disruptive Events

This research focuses on the recovery phase of transportation systems after a disruptive event, specifically, determining the sequence of restoring damaged roadway links with limited budget. A holistic methodology will be proposed to find the optimal solution considering mobility, accessibility, and equity perspective. It is worth mentioning that the restoration plan optimization for transportation system, considering both mobility and accessibility perspectives, has been studied in the research team's previous work. The mobility and accessibility were indicated as the travel time and unmet demand in the system. A journal paper summarizing the previous research is under review. This proposed research project focuses on modeling Restoration Strategy Optimization (RSO) problem as a multi-objective optimization problem taking mobility, accessibility, and equity into account. To the best knowledge of the PIs, equity feature hasn’t been considered in transportation system restoration problem before. The tasks of this research project include the following: (1) Review literature on transportation equity, select the equity measure that fits the best with the research context or propose a new equity measure for the restoration resource allocation purpose; (2) Formulate the RPO problem considering mobility and accessibility as a bi-objective optimization problem and obtain the Pareto frontier of the optimal solutions; (3) formulate the RPO problem considering three perspectives (mobility, accessibility, and equity) as an optimization (of equity measure) over the frontier (of the bi-objective optimization problem) problem and design solution algorithms for this problem; and (4) Conduct a case study to compare the performance of various equity measures and validate the proposed problem formulation and solution algorithms. The team will involve stakeholders throughout the project period to guarantee that performance measurement and problem formulation can be built upon with their real field experience and to ensure that the research output will be practically applicable.