Optimization modelingOptimization problems appear in industrial applications from manufacturing and distribution to healthcare. However, most such problems are still solved heuristically by hand rather than optimally by state-of-the-art solvers, as the expertise required to formulate and solve these problems limits the widespread adoption of optimization tools and techniques. My work has developed several tools to simplify optimization modeling. Most recently, we released a Large Language Model (LLM)-based agent to formulate and solve MILP problems from natural language descriptions. Talks
Software
PapersLLMs for Cold-Start Cutting Plane Separator Configuration ``It Was a Magical Box'': Understanding Practitioner Workflows and Needs in Algebraic characterization of equivalence between optimization algorithms OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale OptiMUS: Scalable Optimization Modeling Using MIP Solvers and Large Language Models OptiMUS: Optimization Modeling Using MIP Solvers and Large Language Models An automatic system to detect equivalence between iterative algorithms Disciplined Multi-Convex Programming Convex Optimization in Julia |