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<item>
  <id>06106556</id>
  <dt>j</dt>
  <an>06106556</an>
  <augroup>
    <au>Gerstl, Enrique</au>
    <au>Mosheiov, Gur</au>
  </augroup>
  <ti>Scheduling job classes on uniform machines.</ti>
  <so>Comput. Oper. Res. 39, No. 9, 1927-1932 (2012).</so>
  <py>2012</py>
  <pu>Elsevier Science Ltd. (Pergamon), Oxford</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>scheduling</ut>
    <ut>uniform machines</ut>
    <ut>earliness</ut>
    <ut>tardiness</ut>
    <ut>minmax</ut>
    <ut>heuristics</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1016/j.cor.2011.08.004</li>
  </ligroup>
  <abgroup>
    <ab>Summary: We study a scheduling problem with job classes on parallel uniform machines. All the jobs of a given class share a common due-date. General, non-decreasing and class-dependent earliness and tardiness cost functions are assumed. Two objectives are considered: (i) minmax, where the scheduler is required to minimize the maximum earliness/tardiness cost among all the jobs and (ii) minmax-minsum, where the scheduler minimizes the sum of the maximum earliness/tardiness cost in all job classes. The problem is easily shown to be NP-hard, and we focus here on the introduction of simple heuristics. We introduce LPT (Largest Processing Time first)-based heuristics for the allocation of jobs to machines within each class, followed by a solution of an appropriate non-linear program, which produces for this job allocation an optimal schedule of the classes. We also propose a lower bound, based on balancing the load on the machines. Our numerical tests indicate that the heuristics result in very small optimality gaps.</ab>
    <rv></rv>
  </abgroup>
</item>