G-LNS: Generative Large Neighborhood Search for LLM-Based Automatic . . . In this work, we propose G-LNS, a generative evolutionary framework that extends LLM-based AHD to the automated design of Large Neighborhood Search (LNS) operators Unlike prior methods that evolve heuristics in isolation, G-LNS leverages LLMs to co-evolve tightly coupled pairs of destroy and repair operators
G-LNS: Generative Large Neighborhood Search for LLM-Based Automatic . . . We propose G-LNS, an evolutionary framework that extends LLM-based AHD to the automated design of Large Neighborhood Search (LNS) operators, enabling structural solution perturbation beyond constructive rules and fixed local moves
G-LNS: Generative Large Neighborhood Search for LLM-Based Automatic . . . G-LNS (Generative Large Neighborhood Search) represents a breakthrough in automated algorithm design, leveraging Large Language Models to automatically create Large Neighborhood Search operators for combinatorial optimization problems