Comparative Analysis of Metaheuristics Techniques for Trade Data Harmonization

Himadri Khargharia, Sid Shakya, Dymitr Ruta

2023

Abstract

The harmonization of trade data from two datasets containing different and distinct categories poses a challenging real-world problem. To address this issue, we model it as an optimization problem and investigate the effectiveness of various metaheuristic techniques in achieving optimal or near-optimal solutions. Particularly, we analyze the performance of Genetic Algorithm (GA), Population-based Incremental Learning (PBIL), DEUM, and Simulated Annealing (SA) in terms of best fitness, scalability, and their respective strengths and weaknesses. We explore multiple instances of the trade data harmonisation problem of different sizes to assess the applicability of these techniques in mitigating trade volume disparities. By examining the outcomes, our research offers valuable insights into the suitability of metaheuristic techniques for this problem.

Paper Citation

in Harvard Style

Khargharia H., Shakya S. and Ruta D. (2023). Comparative Analysis of Metaheuristics Techniques for Trade Data Harmonization. In Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: ECTA; ISBN 978-989-758-674-3, SciTePress, pages 206-213. DOI: 10.5220/0012176600003595

in Bibtex Style

@conference{ecta23,
author={Himadri Khargharia and Sid Shakya and Dymitr Ruta},
title={Comparative Analysis of Metaheuristics Techniques for Trade Data Harmonization},
booktitle={Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: ECTA},
year={2023},
pages={206-213},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012176600003595},
isbn={978-989-758-674-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: ECTA
TI - Comparative Analysis of Metaheuristics Techniques for Trade Data Harmonization
SN - 978-989-758-674-3
AU - Khargharia H.
AU - Shakya S.
AU - Ruta D.
PY - 2023
SP - 206
EP - 213
DO - 10.5220/0012176600003595
PB - SciTePress