A code-graph and correction-based LLM search framework outperforms full-algorithm generation at equal token budgets on three combinatorial optimization problems.
Optimind: Teaching llms to think like optimization experts
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
years
2026 5roles
background 2polarities
background 2representative citing papers
Graph-grounded optimization sources problem elements from knowledge graphs and shows Rao-family metaheuristics plus OR-tools perform differently across seven real-world KG-backed problems while surfacing data issues.
Regression models fit observed LP solver runtimes well within instance classes, but asymptotic growth rates differ substantially across simplex, interior-point, and PDHG methods.
A survey compiling roles, applications, benchmarks, challenges, and future directions for large language models in operations research.
citing papers explorer
-
Budget-Efficient Automatic Algorithm Design via Code Graph
A code-graph and correction-based LLM search framework outperforms full-algorithm generation at equal token budgets on three combinatorial optimization problems.
-
Graph-Grounded Optimization: Rao-Family Metaheuristics, Classical OR, and SLM-Driven Formulation over Knowledge Graphs
Graph-grounded optimization sources problem elements from knowledge graphs and shows Rao-family metaheuristics plus OR-tools perform differently across seven real-world KG-backed problems while surfacing data issues.
-
Empirical Asymptotic Runtime Analysis of Linear Programming Algorithms
Regression models fit observed LP solver runtimes well within instance classes, but asymptotic growth rates differ substantially across simplex, interior-point, and PDHG methods.
-
Large Language Models for Operations Research: A Comprehensive Survey
A survey compiling roles, applications, benchmarks, challenges, and future directions for large language models in operations research.
- Democratizing Large-Scale Re-Optimization with LLM-Guided Model Patches