Regression mapping from instance features to offline-tuned parameters improves Bilevel Late Acceptance Hill Climbing solutions by 0.28% on average over global tuning for the electric capacitated vehicle routing problem.
Learning instance- specific predictive models
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Instance-Aware Parameter Configuration in Bilevel Late Acceptance Hill Climbing for the Electric Capacitated Vehicle Routing Problem
Regression mapping from instance features to offline-tuned parameters improves Bilevel Late Acceptance Hill Climbing solutions by 0.28% on average over global tuning for the electric capacitated vehicle routing problem.