Duality theory in linear optimization and its extensions - formally verified

πŸ“… 2024-09-12
πŸ›οΈ arXiv.org
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The formal foundations of linear optimization duality theory remain underdeveloped, particularly regarding rigorous, machine-checkable verification. Method: We develop a sound and extensible, machine-verifiable framework in Lean 4, leveraging dependent types and algebraic structure modeling to formalize Farkas’ lemma and its variants over general ordered fields. Crucially, we extend duality theory to generalized linear inequality systems with coefficients in the extended reals (including ±∞), rigorously constructing the extended real number system and its order structure. Contributions: (1) The first complete, machine-checked formalization in Lean 4 of multiple Farkas-type theorems, together with precise necessary and sufficient conditions over arbitrary ordered fields; (2) The first mathematical modeling and formal verification of duality theory accommodating infinite coefficients; (3) A foundational, highly reliable basis for verifying optimization algorithms and building trustworthy mathematical libraries.

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πŸ“ Abstract
Farkas established that a system of linear inequalities has a solution if and only if we cannot obtain a contradiction by taking a linear combination of the inequalities. We state and formally prove several Farkas-like theorems over linearly ordered fields in Lean 4. Furthermore, we extend duality theory to the case when some coefficients are allowed to take ``infinite values''.
Problem

Research questions and friction points this paper is trying to address.

Formally verify Farkas-like theorems in Lean 4
Extend duality theory to infinite coefficients
Analyze linear inequalities over ordered fields
Innovation

Methods, ideas, or system contributions that make the work stand out.

Formally verified Farkas-like theorems
Extended duality theory with Lean 4
Infinite coefficients in linear optimization
M
Martin Dvorak
Institute of Science and Technology Austria
Vladimir Kolmogorov
Vladimir Kolmogorov
IST Austria