Authors
José A Cordero, Antonio J Nebro, Cristóbal Barba-González, Juan J Durillo, José García-Nieto, Ismael Navas-Delgado, José F Aldana-Montes
Publication date
2016
Conference
Machine Learning, Optimization, and Big Data: Second International Workshop, MOD 2016, Volterra, Italy, August 26-29, 2016, Revised Selected Papers 2
Pages
106-117
Publisher
Springer International Publishing
Description
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.
Scholar articles
JA Cordero, AJ Nebro, C Barba-González, JJ Durillo… - Machine Learning, Optimization, and Big Data: Second …, 2016