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arxiv: 0902.4304 · v2 · pith:6EFSUCPUnew · submitted 2009-02-25 · 🧮 math.PR

Load optimization in a planar network

classification 🧮 math.PR
keywords allocationsasymptoticlargeallocationanalyzeloadsnetworknumbers
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We analyze the asymptotic properties of a Euclidean optimization problem on the plane. Specifically, we consider a network with three bins and $n$ objects spatially uniformly distributed, each object being allocated to a bin at a cost depending on its position. Two allocations are considered: the allocation minimizing the bin loads and the allocation allocating each object to its less costly bin. We analyze the asymptotic properties of these allocations as the number of objects grows to infinity. Using the symmetries of the problem, we derive a law of large numbers, a central limit theorem and a large deviation principle for both loads with explicit expressions. In particular, we prove that the two allocations satisfy the same law of large numbers, but they do not have the same asymptotic fluctuations and rate functions.

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