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<item>
  <id>05872754</id>
  <dt>j</dt>
  <an>05872754</an>
  <augroup>
    <au>Alenezy, Eiman Jadaan</au>
    <au>Al-Dubaibi, Aisha</au>
    <au>Alhamad, Khalid Moh.</au>
  </augroup>
  <ti>Greedy heuristics to solve the capacitated facility location problem.</ti>
  <so>Far East J. Appl. Math. 48, No. 2, 141-154 (2010).</so>
  <py>2010</py>
  <pu>Pushpa Publishing House, Allahabad, Uttar Pradesh, India</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>FLP</ut>
    <ut>CFLP</ut>
    <ut>UCFLP</ut>
    <ut>greedy heuristics</ut>
    <ut>cut off point</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>http://pphmj.com/abstract/5518.htm</li>
  </ligroup>
  <abgroup>
    <ab>Summary: The facility location problem has been the focus of much research in the Operational Research literature. We investigate solution approaches for large instances of the capacitated facility location problem (CFLP). We introduce a new tightening constraint and dual estimates that lead to improved lower bounds (LB). In our computer environment, we describe a number of greedy heuristics that provide good upper bound solutions with a lower bound from a comparative point of view. We show that for small instances of the CFLP, it is effective to have very tight linking constraints. We report results that illustrate the trade off between these constraints, solution time, and solution quality. We detail some techniques that improve the computational running time with no loss in solution quality. Also we show through solving larger instances of the CFLP that our algorithm scales up well in terms of both computational time and solution quality. Moreover, we develop a sparse technology technique in implementing our algorithm and a flexible computer environment.</ab>
    <rv></rv>
  </abgroup>
</item>