Abstract: A method comprising using at least one hardware processor for: receiving a multi-objective optimization problem; projecting a Pareto frontier of candidate solutions for said multi-objective optimization problem to a hyperplane; decomposing said hyperplane into multiple Voronoi regions each associated with a candidate solution of said candidate solutions; determining a robustness degree for each candidate solution of said candidate solutions, by computing a hypervolume for each region of said multiple Voronoi regions; and ranking said candidate solutions based on the robustness degree.

Abstract: A method comprising using at least one hardware processor for: receiving a multi-objective optimization problem; projecting a Pareto frontier of candidate solutions for said multi-objective optimization problem to a hyperplane; decomposing said hyperplane into multiple Voronoi regions each associated with a candidate solution of said candidate solutions; determining a robustness degree for each candidate solution of said candidate solutions, by computing a hypervolume for each region of said multiple Voronoi regions; and ranking said candidate solutions based on the robustness degree.

Abstract: A method of visualizing a plurality of designs which comply with a plurality of objectives. The method comprises acquiring a plurality of designs each represented by sequential multivariate data indicative of a compliance with a plurality of objectives, generating an objective anchored based self-organizing map (SOM) having a plurality of objective anchors and maps the plurality of designs in an objective space, and outputting the objective anchored based SOM. Each objective anchor is associated with one of the plurality of objectives, each the design is visualized in the objective anchored based SOM by an indicator which the distance thereof from each the objective anchors is indicative of a compliance thereof with a respective the associated objective in relation to other of the plurality of objectives.

Abstract: Systems and methods for detecting leaks in a fluid distribution network are provided. In one embodiment, the method includes calculating value of non-revenue fluid. Further, the method includes receiving data corresponding to pressure from pressure sensors in the fluid distribution network and receiving data corresponding to flow from flow sensors in the fluid distribution network. Furthermore, the method includes estimating pressure values at the pressure sensors and estimating flow values at the flow sensors. The received data and estimated values of respective sensors for corresponding time periods are compared. Existence of leak in the fluid distribution network is detected if the value of non-revenue fluid is non-zero. One or more leak spots are located, if a leak is detected, by solving an optimization problem.

Abstract: A method of visualizing a plurality of designs which comply with a plurality of objectives. The method comprises acquiring a plurality of designs each represented by sequential multivariate data indicative of a compliance with a plurality of objectives, generating an objective anchored based self-organizing map (SOM) having a plurality of objective anchors and maps the plurality of designs in an objective space, and outputting the objective anchored based SOM. Each objective anchor is associated with one of the plurality of objectives, each the design is visualized in the objective anchored based SOM by an indicator which the distance thereof from each the objective anchors is indicative of a compliance thereof with a respective the associated objective in relation to other of the plurality of objectives.

Abstract: Systems and methods for detecting leaks in a fluid distribution network are provided. In one embodiment, the method includes calculating value of non-revenue fluid. Further, the method includes receiving data corresponding to pressure from pressure sensors in the fluid distribution network and receiving data corresponding to flow from flow sensors in the fluid distribution network. Furthermore, the method includes estimating pressure values at the pressure sensors and estimating flow values at the flow sensors. The received data and estimated values of respective sensors for corresponding time periods are compared. Existence of leak in the fluid distribution network is detected if the value of non-revenue fluid is non-zero. One or more leak spots are located, if a leak is detected, by solving an optimization problem.