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This study aims to extend the existing climate-change-induced flood mitigation research. We introduce an at-risk network to evaluate optimal cost–benefit strategies for creating dikes and levees to mitigate flood hazard over multiple years. Our proposed model includes the expected flood costs, estimated using possible climate-change-induced sea-level states throughout the planning horizon, and the investment costs for developing dikes and levees via land elevations across the at-risk network. Further, given the limitations on infrastructure investment, our model incorporates a budget constraint. The problem is modeled as a multistage stochastic program with recourse that minimizes overall expected costs over the planning horizon. Exploiting open-source and freely accessible data sets, the flood risk mitigation model elaborated here can be applied to most urban coastal situations due to its general nature. Using Boston as a case study, our proposed method resulted in a cost reduction of as much as 92.2%, with an average of 63.2%, compared to a "do nothing" strategy in a simulation-based experiment. Under a high sea-level rise scenario, the average cost savings observed by implementing the solution suggested by our model could be even 15% higher. This proposed approach offers decision-makers a tool to frequently assess the costs and risks faced by their cities enabling them to effectively mitigate the potential flooding risks. [ABSTRACT FROM AUTHOR]

We study the minimum vertex blocker clique problem (VBCP),1 which is to remove a subset of vertices of minimum cardinality in a weighted undirected graph, such that the maximum weight of a clique in the remaining graph is bounded above by a given integer r ≥ 1. Cliques are among the most popular concepts used to model cohesive clusters in different graph-based applications, such as social, biological, and communication networks. The general case of VBCP on weighted graphs is known to be NP-hard, and we show that the special case on unweighted graphs is also NP-hard for any fixed integer r ≥ 1. We present an analytical lower bound on the cardinality of an optimal solution to VBCP, as well as formulate VBCP as a linear 0-1 program with an exponential number of constraints. Facet-inducing inequalities for the convex hull of feasible solutions to VBCP are also identified. Furthermore, we develop the first exact algorithm for solving VBCP, which solves the proposed formulation by using a row generation approach. Computational results obtained by utilizing this algorithm on a test-bed of randomly generated instances are also provided. © 2014 Wiley Periodicals, Inc. NETWORKS, Vol. 64(1), 48-64 2014 [ABSTRACT FROM AUTHOR]