Multitasking via alternate and shared processing: Algorithms and complexity

Nicholas G. Hall, Joseph Y.T. Leung, Chung Lun Li

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


This work is motivated by disruptions that occur when jobs are processed by humans, rather than by machines. For example, humans may become tired, bored, or distracted. This paper presents two scheduling models with multitasking features. These models aim to mitigate the loss of productivity in such situations. The first model applies "alternate period processing" and aims either to allow workers to take breaks or to increase workers' job variety. The second model applies "shared processing" and aims to allow workers to share a fixed portion of their processing capacities between their primary tasks and routine activities. For each model, we consider four of the most widely studied and practical classical scheduling objectives. Our purpose is to study the complexity of the resulting scheduling problems. For some problems, we describe a fast optimal algorithm, whereas for other problems an intractability result suggests the probable nonexistence of such an algorithm.

Original languageEnglish (US)
Pages (from-to)41-58
Number of pages18
JournalDiscrete Applied Mathematics
StatePublished - Jul 31 2016

All Science Journal Classification (ASJC) codes

  • Discrete Mathematics and Combinatorics
  • Applied Mathematics


  • Efficient algorithm
  • Intractability
  • Motivations for multitasking
  • Scheduling


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