Boosting an evolution strategy with a preprocessing step: application to group scheduling problem in directional sensor networks

dc.contributor.author Srivastava, Gaurav
dc.contributor.author Singh, Alok
dc.date.accessioned 2022-03-27T05:52:32Z
dc.date.available 2022-03-27T05:52:32Z
dc.date.issued 2018-12-01
dc.description.abstract This paper presents a two-membered evolution strategy based approach to address the total rotation minimization problem (TRMP) pertaining to directional sensor networks. TRMP is an NP-hard problem. Performance of the proposed approach is enhanced by employing a pre-processing step that utilizes a constructive heuristic and the concept of opposite solutions. We have compared our approach with the best approach available in the literature. The experimental results demonstrate our approach to be highly effective with substantial gain in terms of solution quality, in comparison to the best approach available in the literature. However, our approach requires more time in comparison to this approach.
dc.identifier.citation Applied Intelligence. v.48(12)
dc.identifier.issn 0924669X
dc.identifier.uri 10.1007/s10489-018-1252-9
dc.identifier.uri http://link.springer.com/10.1007/s10489-018-1252-9
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8537
dc.subject Directional sensor networks
dc.subject Evolution strategy
dc.subject Group scheduling
dc.subject Total rotation minimization problem
dc.subject Wireless sensor networks
dc.title Boosting an evolution strategy with a preprocessing step: application to group scheduling problem in directional sensor networks
dc.type Journal. Article
dspace.entity.type
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