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Comparison of a Metaheuristic Algorithm and Enhanced Hybrid Algorithms for Inverse Problem in Computed Tomography

  • Silesian University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents an inverse problem in computed tomography using a simplified simulator operating in a two-dimensional space and proposes methods for solving it. The solutions discussed are based on a metaheuristic algorithm—the Group Teaching Optimization Algorithm (GTOA)—as well as a hybrid approach that combines this metaheuristic with two deterministic algorithms: Nelder-Mead (NM) and Hooke-Jeeves (HJ). The study includes performance evaluations of each algorithm, accompanied by graphical representations and a direct comparison of fitness function values and computation times for each solution. The results demonstrate that the hybrid approach consistently produced solutions of comparable or superior quality, with one hybrid instance significantly outperforming the standalone GTOA. Additionally, the hybrid algorithms required substantially less computation time, ranging from 32% to 85% of the time taken by GTOA.

Original languageEnglish
Title of host publicationInformation and Software Technologies - 31st International Conference, ICIST 2025, Proceedings
EditorsAudrius Lopata, Daina Gudoniene, Jonas Ceponis
PublisherSpringer Science and Business Media Deutschland GmbH
Pages185-194
Number of pages10
ISBN (Print)9783032168078
DOIs
Publication statusPublished - 2026
Event31st International Conference on Information and Software Technologies, ICIST 2025 - Kaunas, Lithuania
Duration: 16 Oct 202517 Oct 2025

Publication series

NameCommunications in Computer and Information Science
Volume2871 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference31st International Conference on Information and Software Technologies, ICIST 2025
Country/TerritoryLithuania
CityKaunas
Period16/10/2517/10/25

Keywords

  • computed tomography
  • hybrid algorithm
  • inverse problem
  • metaheuristic algorithm
  • optimization

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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