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    <journal-meta>
      <journal-id journal-id-type="nlm-ta">REA press</journal-id>
      <journal-id journal-id-type="publisher-id">null</journal-id>
      <journal-title>REA press</journal-title><issn pub-type="ppub"> 3042-2248</issn><issn pub-type="epub"> 3042-2248</issn><publisher>
      	<publisher-name>REA press</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">https://doi.org/10.22105/maa.v1i1.18</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Grey wolf optimization algorithm, Bees algorithm, Biogeography-based optimization algorithm, Chicken swarm optimization algorithm‎, Criteria functions</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>Comparing the Performance of the Wolf Algorithm with Three other Meta-Heuristic Algorithms (Bees, Biogeography-Based, Chicken Swarm)</article-title><subtitle>Comparing the Performance of the Wolf Algorithm with Three other Meta-Heuristic Algorithms (Bees, Biogeography-Based, Chicken Swarm)</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Dalili Yazdi</surname>
		<given-names>Hoda </given-names>
	</name>
	<aff>Department of Industrial Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran‎.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Tavakkoli Moghaddam</surname>
		<given-names>Reza  </given-names>
	</name>
	<aff>Department of Industrial Engineering, University of Tehran, Tehran, Iran‎.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Bolhasani</surname>
		<given-names>Golriz </given-names>
	</name>
	<aff>Department of Industrial Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran‎.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>08</month>
        <year>2024</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>09</day>
        <month>08</month>
        <year>2024</year>
      </pub-date>
      <volume>1</volume>
      <issue>1</issue>
      <permissions>
        <copyright-statement>© 2024 REA Press</copyright-statement>
        <copyright-year>2024</copyright-year>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p></license>
      </permissions>
      <related-article related-article-type="companion" vol="2" page="e235" id="RA1" ext-link-type="pmc">
			<article-title>Comparing the Performance of the Wolf Algorithm with Three other Meta-Heuristic Algorithms (Bees, Biogeography-Based, Chicken Swarm)</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			Nowadays, meta-heuristic algorithms have made significant contributions to achieving approximate solutions to optimization problems. It is important to choose a suitable algorithm for each problem, as an algorithm can be appropriate for one type of problem and, at the same time, inappropriate for another one. In this paper, an attempt has been made to compare the Grey Wolf Optimization (GWO) algorithm with 3 modern optimization algorithms (bees algorithm, Biogeography-Based Optimization (BBO) algorithm and Chicken Swarm Optimization (CSO) algorithm). By utilizing 9 criteria functions, the performances of these algorithms in terms of reaching the global optimal point and also the time of reaching have been investigated. In order to make the correct comparison, the selected algorithms are all among the ones which are derived from the foraging behaviors of living organisms.
		</p>
		</abstract>
    </article-meta>
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