We present an algorithm for finding the complete Pareto frontier of biobjective integer programming problems. The method is based on the solution of a finite number of integer programs, each of them returning a Pareto optimal point. The feasible sets of the integer programs are built from the original feasible set, by adding cuts that separate efficient solutions.
Multiobjective mixed integer convex optimization refers to mathematical programming problems where more than one convex objective function needs to be optimized simultaneously and some of the variables are constrained to take integer values. We present a branch-and-bound method based on the use of properly defined lower bounds. We do not simply rely on convex relaxations, but we build linear outer approximations of the image set in an adaptive way.
Rising of the sea level and/or heavy rainfall intensification significantly enhance the risk of flooding in low-lying coastal reclamation areas. Therefore, there is a necessity to assess whether channel hydraulic networks and pumping systems are still efficient and reliable in managing risks of flooding in such areas in the future. This study addresses these issues for the pumping system of the Mazzocchio area, which is the most depressed area within the Pontina plain, a large reclamation region in the south of Lazio (Italy).
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