LAUSR

Infrastructure networks can be damaged during earthquakes. These damaged links can disrupt network operations resulting in significant economic and social losses. Depending on the distribution and extent of damage, and constraints on resources, decision-makers must decide how best to restore a network. Their aim is typically to minimize impacts to the community while negotiating competing objectives of multiple stakeholders, for example, minimizing costs, travel delays and environmental impacts. Thus, restoration decision-making is necessarily complex requiring input from multiple stakeholders throughout the decision-making process. Much of the literature has adopted point-based approaches to restoration whereby algorithms are used to identify solution(s) without broad exploration of the design space. In this paper, a set-based approach is developed following the “Design by Shopping” paradigm in which a full enumeration of restoration designs is generated and visualized allowing decision-makers to broadly “shop” the design space and eliminate the worst designs based on evolving preferences. The merits of set-based design are broad exploration of the design space, design freedom in the initial stages of decision–making, and applying constraints throughout the set-reduction process.