A graph neural network learns to approximate altruistic robot transfers across heterogeneous teams using Hamilton's rule, achieving near-optimal allocation in simulated firefighting scenarios.
Machine learning for combinato- rial optimization: A methodological tour d’horizon
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Survey organizing LLM uses for VRP into modeler, designer, and coordinator roles, covering variants, solvers, benchmarks, and two experiments.
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.
citing papers explorer
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Learning Altruistic Collaboration in Heterogeneous Multi-Team Systems
A graph neural network learns to approximate altruistic robot transfers across heterogeneous teams using Hamilton's rule, achieving near-optimal allocation in simulated firefighting scenarios.
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Vehicle Routing Problem Meets Large Language Models: An Overview and Perspectives
Survey organizing LLM uses for VRP into modeler, designer, and coordinator roles, covering variants, solvers, benchmarks, and two experiments.
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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.