Abstract
AbstractNumerical and symbolic methods for optimization are used extensively in engineering, industry, and finance. Various methods are used to reduce problems of interest to ones that are amenable to solution by these methods. We develop a framework for designing and applying such reductions, using the Lean programming language and interactive proof assistant. Formal verification makes the process more reliable, and the availability of an interactive framework and ambient mathematical library provides a robust environment for constructing the reductions and reasoning about them.
Publisher
Springer Nature Switzerland
Reference44 articles.
1. Agrawal, A., Verschueren, R., Diamond, S., Boyd, S.: A rewriting system for convex optimization problems. J. Control and Decision 5(1), 42–60 (2018)
2. Akbarpour, B., Abdel-Hamid, A.T., Tahar, S., Harrison, J.: Verifying a synthesized implementation of IEEE-754 floating-point exponential function using HOL. Comput. J. 53(4), 465–488 (2010). https://doi.org/10.1093/comjnl/bxp023
3. Allamigeon, X., Katz, R.D.: A formalization of convex polyhedra based on the simplex method. J. Autom. Reason. 63(2), 323–345 (2019)
4. Bachoc, C., Vallentin, F.: New upper bounds for kissing numbers from semidefinite programming. J. Amer. Math. Soc. 21(3), 909–924 (2008). https://doi.org/10.1090/S0894-0347-07-00589-9
5. Baudin, P., Cuoq, P., Filliâtre, J.C., Marché, C., Monate, B., Moy, Y., Prevosto, V.: Acsl: ANSI / ISO c specification language (2020), https://frama-c.com/html/acsl.html, version 1.17
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