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Updated: Sep 9, 2025

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
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Dyadic linear programming and extensions.

Ahmad Abdi1, Gérard Cornuéjols2, Bertrand Guenin3

  • 1Department of Mathematics, London School of Economics, London, England, UK.

Mathematical Programming
|September 4, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a method to efficiently solve dyadic linear programs, which are crucial for accurate computer computations. The research provides polynomial-time algorithms and bounds for dyadic rational solutions in linear programming.

Keywords:
Dense abelian subgroupDyadic rationalFloating-point arithmeticInteger programmingLinear programmingPolynomial algorithm

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Area of Science:

  • Numerical Analysis
  • Computational Mathematics
  • Optimization Theory

Background:

  • Dyadic rational numbers, defined as p/2^k, offer exact finite binary representations.
  • These numbers are vital for precise floating-point arithmetic in computational tasks.
  • A dyadic vector comprises elements that are all dyadic rationals.

Purpose of the Study:

  • To investigate the existence and computation of dyadic optimal solutions for linear programs.
  • To develop efficient algorithms for solving dyadic linear programs.

Main Methods:

  • Formulating and analyzing linear programs with dyadic constraints and solutions.
  • Developing polynomial-time algorithms tailored for dyadic rational arithmetic.
  • Establishing bounds on solution support size and denominator magnitude.

Main Results:

  • Demonstration that dyadic linear programs can be solved in polynomial time.
  • Derivation of bounds for the support size and denominators of dyadic solutions.
  • Identification of key properties (closure under addition/negation, density) enabling dyadic LP solutions.

Conclusions:

  • Dyadic linear programs are solvable efficiently, with guaranteed bounds on solution characteristics.
  • The algorithmic framework can be extended to broader classes of problems beyond strictly dyadic rationals.