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An evolutionary approach to load balancing parallel computations

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dc.contributor.author Mansour, Nashat
dc.contributor.author Fox, Geoffrey C.
dc.date.accessioned 2018-05-29T12:54:01Z
dc.date.available 2018-05-29T12:54:01Z
dc.date.copyright 1991 en_US
dc.date.issued 2018-05-29
dc.identifier.uri http://hdl.handle.net/10725/7956
dc.description.abstract We present a new approach to balancing the workload in a multicomputer. It is based on a genetic algorithm that combines a number of design choices in order to ameliorate the problem of premature convergence. The genetic algorithm is further hybridized by including a hill climbing procedure which significantly improves the efficiency of the evolution. Moreover, it makes use of problem specific information to evade computational costs and to reinforce favorable aspects of the genetic search. The experimental results show that the hybrid genetic algorithm can find solutions that are very close to the optimum. en_US
dc.language.iso en en_US
dc.title An evolutionary approach to load balancing parallel computations en_US
dc.type Conference Paper / Proceeding en_US
dc.author.school SAS en_US
dc.author.idnumber 198629170 en_US
dc.author.department Computer Science and Mathematics en_US
dc.description.embargo N/A en_US
dc.identifier.ctation Fox, G. C., & Mansour, N. " An Evolutionary Approach to Load Balancing Parallel Computations. In Proceedings of Sixth Distributed Memory Computing Conference (pp. 200-203). en_US
dc.author.email nmansour@lau.edu.lb en_US
dc.conference.date May 1, 1991 en_US
dc.conference.pages 200-203 en_US
dc.conference.title Proceedings of the Sixth Distributed Memory Computing Conference en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=633124 en_US
dc.orcid.id https://orcid.org/0000-0002-3603-8284 en_US
dc.publication.date 1991 en_US
dc.author.affiliation Lebanese American University en_US


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