mlsanityData to 7 Oct 2026

When Large Language Model Meets Optimization

arXiv 2405.10098 ↗First posted 16 May 2024cs.NEcited by 22

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Abstract (arXiv)

Optimization algorithms and large language models (LLMs) enhance decision-making in dynamic environments by integrating artificial intelligence with traditional techniques. LLMs, with extensive domain knowledge, facilitate intelligent modeling and strategic decision-making in optimization, while optimization algorithms refine LLM architectures and output quality. This synergy offers novel approaches for advancing general AI, addressing both the computational challenges of complex problems and the application of LLMs in practical scenarios. This review outlines the progress and potential of combining LLMs with optimization algorithms, providing insights for future research directions.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 May 2024.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 14; 2026: 7.

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  1. 2024A Systematic Survey on Large Language Models for Algorithm Designcited by 65
  2. 2025Large Language Models for Combinatorial Optimization: A Systematic Reviewcited by 18
  3. 2025Decision Information Meets Large Language Models: The Future of Explainable Operations Researchcited by 9
  4. 2025EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulationscited by 9
  5. 2025Optimizing Prompt Sequences using Monte Carlo Tree Search for LLM-Based Optimizationcited by 9
  6. 2025A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solvingcited by 9
  7. 2025EvoCut: Strengthening Integer Programs via Evolution-Guided Language Modelscited by 8
  8. 2025SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modelingcited by 8
  9. 2025Combinatorial Optimization for All: Using LLMs to Aid Non-Experts in Improving Optimization Algorithmscited by 5
  10. 2025Cooperative Design Optimization through Natural Language Interactioncited by 4
  11. 2025Large Language Models in Operations Research: Methods, Applications, and Challengescited by 4
  12. 2025Refining Hybrid Genetic Search for CVRP via Reinforcement Learning-Finetuned LLMcited by 3
10 more
  1. 2025REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Modelscited by 1
  2. 2026Prior Knowledge or Search? A Study of LLM Agents in Hardware-Aware Code Optimizationcited by 1
  3. 2025Optimization Problem Solving Can Transition to Evolutionary Agentic Workflowscited by 0
  4. 2025Instruction Learning Paradigms: A Dual Perspective on White-box and Black-box LLMscited by 0
  5. 2026AgenticPruner: MAC-Constrained Neural Network Compression via LLM-Driven Strategy Searchcited by 0
  6. 2026Enhancing Mathematical Problem Solving in LLMs through Execution-Driven Reasoning Augmentationcited by 0
  7. 2026CHAL: Council of Hierarchical Agentic Languagecited by 0
  8. 2026A novel YOLO26-MoE optimized by an LLM agent for insulator fault detection considering UAV imagescited by 0
  9. 2026LP Mining with LP2Graph: A Use Case for Railway Reschedulingcited by 0
  10. 2026LLMs and Agentic AI Systems for Smart Grids: A Tutorial on Architectures and Applicationscited by 0