Solving Subset Sum Problems using Quantum Inspired Optimization Algorithms with Applications in Auditing and Financial Data Analysis

Many applications in automated auditing and the analysis and consistency check of financial documents can be formulated in part as the subset sum problem: Given a set of numbers and a target sum, find the subset of numbers that sums up to the target. The problem is NP-hard and classical solving algorithms are therefore not practical to use in many real applications.We tackle the problem as a QUBO (quadratic unconstrained binary optimization) problem and show how gradient descent on Hopfield Networks reliably finds solutions for both artificial and real data. We outline how this algorithm can be applied by adiabatic quantum computers (quantum annealers) and specialized hardware (field programmable gate arrays) for digital annealing and run experiments on quantum annealing hardware.

  • Published in:
    International Conference on Machine Learning and Applications
  • Type:
    Inproceedings
  • Authors:
    Biesner, David; Gerlach, Thore; Bauckhage, Christian; Kliem, Bernd; Sifa, Rafet
  • Year:
    2022

Citation information

Biesner, David; Gerlach, Thore; Bauckhage, Christian; Kliem, Bernd; Sifa, Rafet: Solving Subset Sum Problems using Quantum Inspired Optimization Algorithms with Applications in Auditing and Financial Data Analysis, International Conference on Machine Learning and Applications, 2022, https://ieeexplore.ieee.org/document/10068999, Biesner.etal.2022a,

Associated Lamarr Researchers

lamarr institute person Biesner David - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

David Biesner

Autor to the profile
Thore Gerlach - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Thore Gerlach

Scientist to the profile
lamarr institute person Bauckhage Christian - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Christian Bauckhage

Director to the profile
Prof. Dr. Rafet Sifa

Prof. Dr. Rafet Sifa

Principal Investigator Hybrid ML to the profile