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Mostrando ítems 1-8 de 8
Ponencia
Automatic Configuration of NSGA-II with jMetal and irace
(ACM Digital Library, 2019)
jMetal is a Java-based framework for multi-objective optimization with metaheuristics providing, among other features, a wide set of algorithms that are representative of the state-of-the-art. Although it has become a ...
Artículo
A multi-objective interactive dynamic particle swarm optimizer
(Springer, 2020)
Multi-objective optimization deals with problems having two or more conflicting objectives that have to be optimized simulta-neously. When the objectives change somehow with time, the problems become dynamic, and if the ...
Artículo
jMetalSP: A framework for dynamic multi-objective big data optimization
(Elsevier, 2018)
Multi-objective metaheuristics have become popular techniques for dealing with complex optimization problems composed of a number of conflicting functions. Nowadays, we are in the Big Data era, so metaheuristics must be ...
Artículo
Optimizing ligand conformations in flexible protein targets: amulti-objective strategy
(Springer, 2020)
Finding the orientation of a ligand (small molecule) with the lowest binding energy to the macromolecule (receptor) is a complex optimization problem, commonly called ligand–protein docking. This problem has been usually ...
Artículo
Qom—A New Hydrologic Prediction Model Enhanced with Multi-Objective Optimization
(MDPI, 2019)
The efficient calibration of hydrologic models allows experts to evaluate past events in river basins, as well as to describe new scenarios and predict possible future floodings. A difficulty in this context is the need ...
Artículo
jMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristics
(Elsevier, 2019)
This paper describes jMetalPy, an object-oriented Python-based framework for multi-objective optimization with metaheuristic techniques. Building upon our experiences with the well-known jMetal framework, we have developed ...
Ponencia
Multi-Objective Big Data Optimization with jMetal and Spark
(Springer, 2017)
Big Data Optimization is the term used to refer to optimiza- tion problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster ...
Ponencia
About Designing an Observer Pattern-Based Architecture for a Multi-objective Metaheuristic Optimization Framework
(Springer, 2018)
Multi-objective optimization with metaheuristics is an active and popular research field which is supported by the availability of software frameworks providing algorithms, benchmark problems, quality indicators and ...