Reinforcement-learned neighborhood operator selection improves variable neighborhood search for vehicle routing with multiple time windows, beating adaptive VNS by 3-15% in route length while running several times faster.
Calibrating 15 years of GOLF data
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abstract
The GOLF resonant scattering spectrophotometer aboard SoHO has now provided 15 years of continuous high precision Sun-as-a-star radial-velocity measurements. This length of time series provides very high resolution in the frequency domain and is combined with very good long-term instrumental stability. These are the requirements for measuring the low-l low-frequency global oscillations of the Sun that will unlock the secrets of the solar core. However, before the scientifically interesting gravity and mixed modes of oscillation fully reveal themselves, a correction and calibration of the whole data set is required. Here we present work towards producing a 15 year GOLF data set corrected for instrumental ageing and thermal variation.
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Learning to Search for Vehicle Routing with Multiple Time Windows
Reinforcement-learned neighborhood operator selection improves variable neighborhood search for vehicle routing with multiple time windows, beating adaptive VNS by 3-15% in route length while running several times faster.