HIGHLIGHTS
- who: Problem and colleagues from the (UNIVERSITY) have published the paper: Learned Upper Bounds for the Time-Dependent Travelling Salesman Problem, in the Journal: (JOURNAL)
- what: The aim of this work is to define tight upper bounds for this by reusing the information gained when solving instances with similar features. The effectiveness of this approach has been assessed through a computational campaign on the real travel time functions of two European cities: Paris and London. The aim of this article is to present a Machine Learning (ML) enhanced upper-bound for the Time-Dependent Travelling . . .
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