Craig Tweedy

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Using the problem of selecting the best location for a meteorological tower as an example, we show that in multi-objective optimization under constraints, the traditional weighted average approach is often inadequate. We also show that natural invariance requirements lead to a more adequate approach – a generalization of Nash's bargaining solution. Case(More)
One of our main challenges in meteorology and environment research is that in many important remote areas, sensor coverage is sparse, leaving us with numerous blind spots. Placement and maintenance of sensors in these areas are expensive. It is therefore desirable to find out how, within a given budget, we can design a sensor network are important(More)
1 Formulation of the Problem Case study. In meteorological and environmental studies, it is important to get additional data from remote locations; see, e.g., [5]. One way of collecting this additional data is to place several different sensors on a single tower. It is therefore important to select the best location of a sophisticated multi-sensor(More)
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