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HEMO: Harness Self-Evolution for Multi-Objective Combinatorial Optimization

Automatic operator design (AOD) has increasingly adopted large language models (LLMs) to generate problem-specific search and variation operators for multi-objective combinatorial optimization (MOCO). Yet most methods evolve the operators while leaving the process that discovers them fixed. This limits adaptation as new Pareto trade-offs and operator interactions change where and how the search…

arxiv.org ·17h ago

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Read the original at arxiv.org →

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