具有凸约束的二次规划的最优性。传感器数据融合的应用

Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997) Pub Date : 2002-07-08 DOI:10.1109/ICIF.2002.1020991

C. Musso, P. Dodin

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引用次数: 0

摘要

从理论上分析了多目标/多传感器领域中可能出现的最大化二次规划。目标是找到使x和给定点y之间的二次距离最小的点x。这个最优点必须位于由线性不等式定义的凸约束区域中。我们给出了这个最优的紧对偶形式的一个表征。这种优化框架可以很有帮助，例如，在多目标编程中，如分散的资源分配。

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Characterization of the optimum of a quadratic program with convex constraints. Application to sensor data fusion

We analyse theoretically a maximisation quadratic program which can arise in multi-target/multi-sensor area. The goal is to find the point x which minimizes the quadratic distance between x and a given point y. This optimum must lie in a convex constrained region defined by linear inequalities. We present a characterisation of this optimum in a compact dual form. This optimisation framework can be helpful, for example, in muti-objective programming like decentralized resource allocation.

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Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)

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