The b-LAHC algorithm sets 9/10 new best-known results on large-scale E-CVRP benchmarks by using a surrogate-guided bilevel framework with fixed parameters.
An efficient threshold acceptance- based multi-layer search algorithm for capacitated electric vehicle rout- ing problem
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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.
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Bilevel Late Acceptance Hill Climbing for the Electric Capacitated Vehicle Routing Problem
The b-LAHC algorithm sets 9/10 new best-known results on large-scale E-CVRP benchmarks by using a surrogate-guided bilevel framework with fixed parameters.
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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.