<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Resource Management and Decision Engineering</JournalTitle>
      <Issn></Issn>
      <Volume>3</Volume>
      <Issue>Serial Number 8</Issue>
      <PubDate PubStatus="epublish">
        <Year>2024</Year>
        <Month>09</Month>
        <Day>30</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Optimization of the Time-Cost-Quality Trade-Off in the Context of the Haftkel Dam Construction Project</ArticleTitle>
    <VernacularTitle>Optimization of the Time-Cost-Quality Trade-Off in the Context of the Haftkel Dam Construction Project</VernacularTitle>
    <FirstPage>135</FirstPage>
    <LastPage>145</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2024</Year>
        <Month>06</Month>
        <Day>16</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;In recent years, the increasing complexity of project implementation, the competitive nature of the business environment, and the constraints on organizational resources have heightened the importance of project management in achieving project objectives. Consequently, during the execution phases of projects, clients seek to enhance quality, reduce execution time and costs, and minimize risks, which constitute their primary goals. This study focuses on optimizing the components of the project management “survival triangle”—time, cost, and quality—in civil engineering projects, specifically through a case study of the Sartiuk Haftkel Reservoir Dam. For this purpose, a genetic algorithm was employed. Optimization was carried out in three separate scenarios, each targeting one of the elements of the survival triangle, and finally, a composite optimization was conducted that considered all three elements simultaneously. The coding related to objective functions and optimization algorithms was performed using MATLAB software. The results indicate the satisfactory performance of the genetic algorithm. Furthermore, for quality index optimization, the genetic algorithm yielded the best optimal solution, and in the composite optimization considering all indices simultaneously, it again provided the most effective result.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">optimization</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">time</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">cost</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">quality</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Sartyrak Haftgol reservoir dam</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalrmde.com/index.php/jrmde/article/download/96/111</ArchiveCopySource>
  </Article>
</ArticleSet>
