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Author (up) Garcia, J.; Altimiras, F.; Pena, A.; Astorga, G.; Peredo, O. pdf  doi
  Title A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling Problems Type
  Year 2018 Publication Complexity Abbreviated Journal Complexity  
  Volume Issue Pages 15 pp  
  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:  
  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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