Multitasking via alternate and shared processing: Algorithms and complexity
Document Type
Article
Publication Date
7-31-2016
Abstract
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.
Identifier
84992297280 (Scopus)
Publication Title
Discrete Applied Mathematics
External Full Text Location
https://doi.org/10.1016/j.dam.2016.03.018
ISSN
0166218X
First Page
41
Last Page
58
Volume
208
Grant
CMMI-0969830
Fund Ref
National Science Foundation
Recommended Citation
Hall, Nicholas G.; Leung, Joseph Y.T.; and Li, Chung Lun, "Multitasking via alternate and shared processing: Algorithms and complexity" (2016). Faculty Publications. 10366.
https://digitalcommons.njit.edu/fac_pubs/10366