DACMO constructs general-purpose parallel algorithm portfolios for multi-objective binary optimization via co-evolution of neural instance representations and LLM-generated operators, performing competitively on four problem classes without problem-specific generators.
LLM- driven instance-specific heuristic generation and selection
3 Pith papers cite this work. Polarity classification is still indexing.
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AHD Agent trains a 4B-parameter LLM via agentic RL to actively use tools for automatic heuristic design, matching or exceeding larger baselines across eight domains with fewer evaluations.
TransGP uses a task-conditioned Transformer to guide genetic programming toward elite heuristics and generate task-specific rules for multitask dynamic flexible job shop scheduling, outperforming standard GP and handcrafted methods in experiments.
citing papers explorer
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General-Purpose Co-Evolutionary Construction of Parallel Algorithm Portfolios for Multi-Objective Binary Optimization
DACMO constructs general-purpose parallel algorithm portfolios for multi-objective binary optimization via co-evolution of neural instance representations and LLM-generated operators, performing competitively on four problem classes without problem-specific generators.
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AHD Agent: Agentic Reinforcement Learning for Automatic Heuristic Design
AHD Agent trains a 4B-parameter LLM via agentic RL to actively use tools for automatic heuristic design, matching or exceeding larger baselines across eight domains with fewer evaluations.
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TransGP: Task-Conditioned Transformer-Guided Genetic Programming for Multitask Dynamic Flexible Job Shop Scheduling
TransGP uses a task-conditioned Transformer to guide genetic programming toward elite heuristics and generate task-specific rules for multitask dynamic flexible job shop scheduling, outperforming standard GP and handcrafted methods in experiments.