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A Rapid Method for Modeling a Variable Cycle Engine
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Minimum flow decomposition in graphs with cycles using integer linear programming.

Fernando H C Dias1, Lucia Williams2, Brendan Mumey3

  • 1Department of Mathematics and Systems Analysis, Aalto University, 02150 Espoo, Finland.

Journal of Global Optimization : an International Journal Dealing with Theoretical and Computational Aspects of Seeking Global Optima and Their Applications in Science, Management and Engineering
|December 22, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces the first exact Integer Linear Programming (ILP) formulation for minimum flow decomposition (MFD) on graphs with cycles. This novel approach provides accurate solutions for complex flow decomposition problems in various scientific fields.

Keywords:
BioinformaticsFlow DecompositionInteger Linear ProgrammingNetwork FlowTransportation Science

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Area of Science:

  • Computer Science
  • Operations Research
  • Bioinformatics
  • Transportation Science

Background:

  • Minimum Flow Decomposition (MFD) is a classical problem, crucial for modeling in Bioinformatics and Transportation.
  • Existing solutions for MFD on graphs with cycles are heuristic or approximate, lacking exactness.
  • The MFD problem is NP-hard even on acyclic graphs, highlighting the complexity of finding exact solutions.

Purpose of the Study:

  • To present the first Integer Linear Programming (ILP) formulation for Minimum Flow Decomposition (MFD) on graphs containing cycles.
  • To address three variants of MFD, focusing on decompositions into paths, cycles, trails, and walks.

Main Methods:

  • Developed novel Integer Linear Programming (ILP) formulations for Minimum Flow Decomposition (MFD) on cyclic graphs.
  • Tested the ILP formulations on three datasets of increasing complexity from Bioinformatics and Transportation.

Main Results:

  • The proposed ILP formulations provide the first exact solutions for MFD on graphs with cycles.
  • All tested instances across diverse datasets were solved within 12 minutes, demonstrating computational efficiency.
  • The study offers a significant advancement over existing heuristic and approximation methods for MFD.

Conclusions:

  • The presented ILP approach offers a robust and exact method for solving Minimum Flow Decomposition problems on cyclic graphs.
  • This work provides a powerful new tool for applications in Bioinformatics, Transportation, and other fields reliant on flow analysis.
  • Freely available implementations facilitate further research and application of these exact MFD solutions.