This work presents a tool that implements data-driven approaches that can dynamically select a smaller number of instances that provide sufficient statistical evidence to evaluate the relative performance of a given set of solvers and makes them readily accessible to solver developers, thus enabling them to obtain swifter feedback on their ideas.
Large language models (LLMs) have recently improved their problem-solving abilities and can solve complex mathematical problems with an increasing accuracy, necessitating the development of more challenging benchmarks. Over the years, the performance of LLMs on several benchmark datasets has also improved, motivating t...
Anurag Dutta, S. Priya, A. Ramamoorthy et al.· AppliedMath· 0 citations
AlgoWorlds is introduced, a benchmark that transforms formally specified combinatorial optimization problems into partially observed decision environments with verifiable global optima, and seven leading LLMs are evaluated, including Claude Opus 4.8 and GPT-5.6 Sol.
This paper introduces AESAT (Auto-Evolving SAT solving), a novel neuro-symbolic framework designed to automatically evolve and optimize the heuristic functions of SAT solvers, and represents the first time an LLM-enhanced solver has dominated the world's premier SAT competition.
Mao Luo, Hang Ding, Chumin Li et al.· Proceedings of the Thirty-Fi...· 0 citations
This paper presents a systematic refactoring approach using Claude agentic AI on real-world project-scheduling workloads in a high-performance computing (HPC) environment, where the agent identifies bottlenecks, implements targeted optimizations, and evaluates their effects, while the researcher retains final control.
Combinatorial problems appear in numerous industrial applications. A common approach is to formulate these problems as declarative constraint models that can subsequently be compiled to and solved by a range of back-end solvers. Recent work shows that Large Language Models (LLMs) can produce correct models from natural...
This study presents a simulation framework designed to evaluate the behavioral effectiveness of various automated solvers, and introduces AlphaSudoku, a hybrid simulation model that integrates probabilistic rules and strategic search.
Vincent Sieso, Ludivine Lasserre, A. Doncescu· International Conference on...· 0 citations
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