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.
MOEA/D: A multiobjective evolutionary algorithm based on decomposition,
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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.