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  <doi_batch_id>aspg-33-4429-1792223344</doi_batch_id>
  <timestamp>20261017074904</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
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  <journal>
   <journal_metadata language="en">
    <full_title>Galoitica: Journal of Mathematical Structures and Applications</full_title>
    <abbrev_title>GJMSA</abbrev_title>
    <issn media_type="electronic">2834-5568</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2026</year>
    </publication_date>
    <journal_volume>
     <volume>13</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Improved Solution Methods for Initial Value Problems of Ordinary Differential Equations Using Advanced Optimization Techniques</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Qasim</given_name>
      <surname>Tayyeh</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Mechanical Techniques,Al-Nasiriya Technical Institute, Southern Technical University, Thi-Qar, Al-Nasiriya 64001, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Initial value problems (IVPs) of ordinary differential equations (ODEs) are ubiquitous in science and engineering applications, and the classical fourth-order Runge–Kutta (RK4) method is by far the most popular solver due to its good accuracy-to-cost ratio. Among all four-stage fourth-order explicit RK methods there are two free node parameters left after satisfying the eight B-series order conditions, thus allowing further systematic enhancements. Here we employ a hybrid multi-seed Particle Swarm Optimization (PSO)-Nelder–Mead algorithm to search for optimal RK node parameters (c₂, c₃) with respect to a minimax normalized objective over eight commonly used nonlinear benchmark problems. The resulting PSO-RK4 method with (c₂ = 0.323665, c₃ = 0.653527) retains both the exact same order of convergence and absolute stability region as the classical RK method called the 3/8-rule, but exhibits reduced maximum global error on each of the eight benchmarks when N = 300; average improvement of 27.9% with gains up to 46.0% on the Bernoulli equation, 29.7% on logistic growth, and 21.3% on exponential. Robustness of these gains with respect to multi-step-size (N = 100, 200, 300, 500) is demonstrated.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2026</year>
    </publication_date>
    <pages>
     <first_page>57</first_page>
     <last_page>75</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">4429</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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    <doi_data>
     <doi>10.54216/GJMSA.130105</doi>
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