A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling Problems
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 applyin...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/8395193 |
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| _version_ | 1832556260688396288 |
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| author | José García Francisco Altimiras Alvaro Peña Gino Astorga Oscar Peredo |
| author_facet | José García Francisco Altimiras Alvaro Peña Gino Astorga Oscar Peredo |
| author_sort | José García |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-08fc3521357846e48a8a2a541db3ac04 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-08fc3521357846e48a8a2a541db3ac042025-02-03T05:45:48ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/83951938395193A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling ProblemsJosé García0Francisco Altimiras1Alvaro Peña2Gino Astorga3Oscar Peredo4Escuela de Ingeniería en Construcción, Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, ChileTelefónica Investigación y Desarrollo, Santiago, ChileEscuela de Ingeniería en Construcción, Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, ChileUniversidad de Valparaíso, 2361864 Valparaíso, ChileTelefónica Investigación y Desarrollo, Santiago, ChileThe 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.http://dx.doi.org/10.1155/2018/8395193 |
| spellingShingle | José García Francisco Altimiras Alvaro Peña Gino Astorga Oscar Peredo A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling Problems Complexity |
| title | A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling Problems |
| title_full | A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling Problems |
| title_fullStr | A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling Problems |
| title_full_unstemmed | A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling Problems |
| title_short | A Binary Cuckoo Search Big Data Algorithm Applied to Large-Scale Crew Scheduling Problems |
| title_sort | binary cuckoo search big data algorithm applied to large scale crew scheduling problems |
| url | http://dx.doi.org/10.1155/2018/8395193 |
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