A swarm intelligence approach to the early/tardy scheduling problem

dc.contributor.author Sundar, Shyam
dc.contributor.author Singh, Alok
dc.date.accessioned 2022-03-27T06:01:20Z
dc.date.available 2022-03-27T06:01:20Z
dc.date.issued 2012-06-01
dc.description.abstract This paper describes an application of artificial bee colony (ABC) algorithm, which is a new swarm intelligence approach, for a version of the single machine early/tardy scheduling problem where no unforced machine idle time is allowed. A local search is used inside the ABC algorithm to further improve the schedules obtained through it. A variant of the basic ABC approach is also considered in this paper where the best solution obtained through ABC algorithm is improved further via an exhaustive local search. We have compared these two approaches with 16 heuristic approaches reported in the literature on existing set of benchmark instances as well as on some large instances. Computational results show the effectiveness of our approaches. © 2011 Elsevier B.V. All rights reserved.
dc.identifier.citation Swarm and Evolutionary Computation. v.4
dc.identifier.issn 22106502
dc.identifier.uri 10.1016/j.swevo.2011.12.002
dc.identifier.uri https://www.sciencedirect.com/science/article/abs/pii/S2210650211000733
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/9126
dc.subject Artificial bee colony algorithm
dc.subject Constrained optimization
dc.subject Early/tardy scheduling
dc.subject Heuristic
dc.subject Swarm intelligence
dc.title A swarm intelligence approach to the early/tardy scheduling problem
dc.type Journal. Article
dspace.entity.type
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