ACO Algorithms to Solve an Electromagnetic Discrete Optimization Problem

Anton Duca, Ibrahim Hameed

2020

Abstract

The paper proposes and studies the efficiency of the ant colony optimization (ACO) algorithms for solving an inverse problem in non-destructive electromagnetic testing (NDET). The inverse problem, which consists in finding the shape and parameters of cracks in conducting plates starting from the signal of an eddy current testing (ECT) probe, is formulated as a discrete optimization problem. Two of the most widely known ant algorithms are adapted and applied to solve the optimization problem. The influence over the optimization algorithms performances of some problem specific local search strategies is also analyzed.

Paper Citation

in Harvard Style

Duca A. and Hameed I. (2020). ACO Algorithms to Solve an Electromagnetic Discrete Optimization Problem. In Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA; ISBN 978-989-758-475-6, SciTePress, pages 115-122. DOI: 10.5220/0009980001150122

in Bibtex Style

@conference{ecta20,
author={Anton Duca and Ibrahim Hameed},
title={ACO Algorithms to Solve an Electromagnetic Discrete Optimization Problem},
booktitle={Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA},
year={2020},
pages={115-122},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009980001150122},
isbn={978-989-758-475-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA
TI - ACO Algorithms to Solve an Electromagnetic Discrete Optimization Problem
SN - 978-989-758-475-6
AU - Duca A.
AU - Hameed I.
PY - 2020
SP - 115
EP - 122
DO - 10.5220/0009980001150122
PB - SciTePress