Presentation
Dynamic Multi-Objective Optimization With jMetal and Spark: a Case Study
Author/s | Cordero, José A.
Nebro, Antonio J. Barba González, Cristóbal Durillo, Juan J. García Nieto, José Manuel Navas Delgado, Ismael Aldana Montes, José F. |
Department | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Publication Date | 2016 |
Deposit Date | 2021-05-06 |
Published in |
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ISBN/ISSN | 978-3-319-51468-0 0302-9743 |
Abstract | Technologies for Big Data and Data Science are receiving increasing research interest nowadays. This paper introduces the prototyping architecture of a tool aimed to solve Big Data Optimization problems. Our tool combines ... Technologies for Big Data and Data Science are receiving increasing research interest nowadays. This paper introduces the prototyping architecture of a tool aimed to solve Big Data Optimization problems. Our tool combines the jMetal framework for multi-objective optimization with Apache Spark, a technology that is gaining momentum. In particular, we make use of the streaming facilities of Spark to feed an optimization problem with data from different sources. We demonstrate the use of our tool by solving a dynamic bi-objective instance of the Traveling Salesman Problem (TSP) based on near real-time traffic data from New York City, which is updated several times per minute. Our experiment shows that both jMetal and Spark can be integrated providing a software platform to deal with dynamic multi-optimization problems. |
Funding agencies | Ministerio de Ciencia e Innovación (MICIN). España Junta de Andalucía |
Project ID. | TIN2011-25840
P11-TIC-7529 P12-TIC-1519 |
Citation | Cordero, J.A., Nebro, A.J., Barba González, C., Durillo, J.J., García Nieto, J.M., Navas Delgado, I. y Aldana Montes, J.F. (2016). Dynamic Multi-Objective Optimization With jMetal and Spark: a Case Study. En MOD 2016: Second International Workshop on Machine Learning, Optimization, and Big Data (106-117), Volterra, Italy: Springer. |
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