Large-Number Optimization: Exact-Arithmetic Mathematical Programming with Integers and Fractions Beyond Any Bit Limits

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Publicat a:Mathematics vol. 13, no. 19 (2025), p. 3190-3230
Autor principal: Kallrath Josef
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MDPI AG
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100 1 |a Kallrath Josef 
245 1 |a Large-Number Optimization: Exact-Arithmetic Mathematical Programming with Integers and Fractions Beyond Any Bit Limits 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Mathematical optimization, in both continuous and discrete forms, is well established and widely applied. This work addresses a gap in the literature by focusing on large-number optimization, where integers or fractions with hundreds of digits occur in decision variables, objective functions, or constraints. Such problems challenge standard optimization tools, particularly when exact solutions are required. The suitability of computer algebra systems and high-precision arithmetic software for large-number optimization problems is discussed. Our first contribution is the development of Python implementations of an exact Simplex algorithm and a Branch-and-Bound algorithm for integer linear programming, capable of handling arbitrarily large integers. To test these implementations for correctness, analytic optimal solutions for nine specifically constructed linear, integer linear, and quadratic mixed-integer programming problems are derived. These examples are used to test and verify the developed software and can also serve as benchmarks for future research in large-number optimization. The second contribution concerns constructing partially increasing subsequences of the Collatz sequence. Motivated by this example, we quickly encountered the limits of commercial mixed-integer solvers and instead solved Diophantine equations or applied modular arithmetic techniques to obtain partial Collatz sequences. For any given number J, we obtain a sequence that begins at <inline-formula>2J−1</inline-formula> and repeats J times the pattern ud: multiply by <inline-formula>3xj+1</inline-formula> and then divide by 2. Further partially decreasing sequences are designed, which follow the pattern of multiplying by <inline-formula>3xj+1</inline-formula> and then dividing by <inline-formula>2m</inline-formula>. The most general J-times increasing patterns (ududd, udududd, …, ududududddd) are constructed using analytic and semi-analytic methods that exploit modular arithmetic in combination with optimization techniques. 
653 |a Cryptography 
653 |a Fractions 
653 |a Software 
653 |a Computer algebra 
653 |a Linear programming 
653 |a Integer programming 
653 |a Mathematical analysis 
653 |a Parameter identification 
653 |a Mathematical programming 
653 |a Optimization 
653 |a Real time 
653 |a Python 
653 |a Systems engineering 
653 |a Diophantine equation 
653 |a Programming languages 
653 |a Arithmetic 
653 |a Exact solutions 
653 |a Algorithms 
653 |a Sequences 
653 |a Mixed integer 
653 |a Libraries 
773 0 |t Mathematics  |g vol. 13, no. 19 (2025), p. 3190-3230 
786 0 |d ProQuest  |t Engineering Database 
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