The Subset Sum Matching Problem

TL;DR

This paper introduces the Subset Sum Matching Problem, a new combinatorial optimization task inspired by financial trade reconciliation, along with algorithms and a benchmark for evaluation.

Contribution

It proposes the SSMP, develops three algorithms including an optimal one, and creates a benchmark for testing their performance.

Findings

The optimal algorithm outperforms suboptimal ones in accuracy.

Benchmark results show varying performance across different instance complexities.

The SSMP effectively models real-world financial reconciliation tasks.

Abstract

This paper presents a new combinatorial optimisation task, the Subset Sum Matching Problem (SSMP), which is an abstraction of common financial applications such as trades reconciliation. We present three algorithms, two suboptimal and one optimal, to solve this problem. We also generate a benchmark to cover different instances of SSMP varying in complexity, and carry out an experimental evaluation to assess the performance of the approaches.