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Author Garcia, J.; Altimiras, F.; Pena, A.; Astorga, G.; Peredo, O.
Title A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling Problems Type
Year 2018 Publication (up) Complexity Abbreviated Journal Complexity
Volume Issue Pages 15 pp
Keywords
Abstract The progress of metaheuristic techniques, big data, and the Internet of things generates opportunities to performance improvements in complex industrial systems. This article explores the application of Big Data techniques in the implementation of metaheuristic algorithms with the purpose of applying it to decision-making in industrial processes. This exploration intends to evaluate the quality of the results and convergence times of the algorithm under different conditions in the number of solutions and the processing capacity. Under what conditions can we obtain acceptable results in an adequate number of iterations? In this article, we propose a cuckoo search binary algorithm using the MapReduce programming paradigm implemented in the Apache Spark tool. The algorithm is applied to different instances of the crew scheduling problem. The experiments show that the conditions for obtaining suitable results and iterations are specific to each problem and are not always satisfactory.
Address [Garcia, Jose; Pena, Alvaro] Pontificia Univ Catolica Valparaiso, Escuela Ingn Construct, Valparaiso 2362807, Chile, Email: joseantonio.garcia@telefonica.com
Corporate Author Thesis
Publisher Wiley-Hindawi Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1076-2787 ISBN Medium
Area Expedition Conference
Notes WOS:000441522300001 Approved
Call Number UAI @ eduardo.moreno @ Serial 897
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