Equitable Scheduling on a Single Machine

Klaus Heeger, Danny Hermelin, George B. Mertzios, Hendrik Molter, Rolf Niedermeier, Dvir Shabtay

Research output: Working paper/PreprintPreprint

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Abstract

We introduce a natural but seemingly yet unstudied generalization of the problem of scheduling jobs on a single machine so as to minimize the number of tardy jobs. Our generalization lies in simultaneously considering several instances of the problem at once. In particular, we have $n$ clients over a period of $m$ days, where each client has a single job with its own processing time and deadline per day. Our goal is to provide a schedule for each of the $m$ days, so that each client is guaranteed to have their job meet its deadline in at least $k \le m$ days. This corresponds to an equitable schedule where each client is guaranteed a minimal level of service throughout the period of $m$ days. We provide a thorough analysis of the computational complexity of three main variants of this problem, identifying both efficient algorithms and worst-case intractability results.
Original languageEnglish
PublisherarXiv:2010.04643 [cs.DM]
StatePublished - 2020

Keywords

  • Computer Science - Discrete Mathematics
  • Computer Science - Data Structures and Algorithms

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