A neural Shortest Path Network approximates Gibbs-sampled routes to make joint facility-location and path optimization scalable, with roughly 6% path-cost gap and large speedups.
7.5 Worst case computational complexity of∇ Y Fβ via(12),(13)isO(N M 4)
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Parametrized Multi-Agent Routing via Deep Attention Models
A neural Shortest Path Network approximates Gibbs-sampled routes to make joint facility-location and path optimization scalable, with roughly 6% path-cost gap and large speedups.