LLM-based optimization framework: An architectural overview
Jozef Kováč, Tomáš Kadavý, Adam Viktorin, Roman Šenkeřík · Array · 2026
This paper provides a detailed analysis of the potential technical and architectural challenges associated with building the FrontEASE software. FrontEASE serves as the web wrapper, utility extension, and user interaction layer for the modular LLM-based optimization framework, EASE (Effortless Algorithmic Solution Evolution). The focus is on the architectural choices made and how this unconventional solution, designed to streamline the use of LLM-based optimization workflows for scientific applications, aligns with best practices in standard software engineering. The primary goal of this paper is to promote and facilitate further experimentation with enterprise-grade architectures for LLM-driven applications. Ultimately, this work aims to guide the development of these products into reliable and maintainable software solutions over the long term.