HMACE: Heterogeneous Multi-Agent Collaborative Evolution for Combinatorial Optimization

ArXi:2605.07214v1 Announce Type: new Large Language Models have recently emerged as a promising paradigm for automated heuristic design for NP-hard combinatorial optimization problems. Despite this progress, existing LLM-based methods typically rely on monolithic workflows constrained by rigid templates, thereby restricting memory-guided exploration and triggering premature convergence to local optima. To design an autonomous and collaborative architecture, we