numerical-optimization-formulation

To convert natural language optimization problems into mathematical formulations, this Skill parses problem statements sentence-by-sentence to classify the problem type as LP, MILP, or QP, and extracts labeled parameters, constraints, decisions, and objectives to produce a structured formulation mapping.

LP, MILP, and QP problem classification in operations research depends on objective structure, variable types, and constraint characteristics. This Skill determines which formulation applies to your optimization problem and enforces specific handling rules, such as QP minimization-only constraints.

Identifying implicit objectives and constraints during optimization text parsing requires resolving ambiguities through multiple interpretations. This Skill labels each sentence explicitly without silently assuming a single interpretation and flags implicit constraints and objectives.

You can use reusable formulation patterns for common optimization structures like cutting stock, trim loss, multi-period inventory capacity timing, and blending with shared mixing. This Skill provides pattern-based modeling guidance to structure these specific formulations.

Quadratic programming formulation limitations include a strict minimization-only handling requirement. This Skill enforces QP minimization-only rules and performs well-posedness checks to ensure the mathematical formulation is valid before providing modeling guidance.

No external APIs or solver interfaces are needed to formulate optimization models. This Skill provides pattern-based formulation guidance and problem parsing entirely through text classification and labeling without relying on any API or interface code.