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SMPSO: A new PSO-based metaheuristic for multi-objective optimization
- Antonio J. Nebro, J. Durillo, J. García-Nieto, C. C. Coello, F. Luna, E. Alba
- Mathematics, Computer ScienceIEEE Symposium on Computational Intelligence in…
- 15 May 2009
A new multi-objective particle swarm optimization algorithm characterized by the use of a strategy to limit the velocity of the particles, called Speed-constrained Multi-Objective PSO (SMPSO), which allows to produce new effective particle positions in those cases in which the velocity becomes too high.
jMetal: A Java framework for multi-objective optimization
This paper describes jMetal, an object-oriented Java-based framework aimed at the development, experimentation, and study of metaheuristics for solving multi-objective optimization problems, and includes two case studies to illustrate the use of jMetal in both solving a problem with a metaheuristic and designing and performing an experimental study.
MOCell: A cellular genetic algorithm for multiobjective optimization
- Antonio J. Nebro, J. Durillo, F. Luna, B. Dorronsoro, E. Alba
- Computer ScienceInt. J. Intell. Syst.
- 1 July 2009
This paper introduces a new cellular genetic algorithm called MOCell, characterized by using an external archive to store nondominated solutions and a feedback mechanism in which solutions from this archive randomly replace existing individuals in the population after each iteration.
AbYSS: Adapting Scatter Search to Multiobjective Optimization
- Antonio J. Nebro, F. Luna, E. Alba, B. Dorronsoro, J. Durillo, A. Beham
- Mathematics, Computer ScienceIEEE Transactions on Evolutionary Computation
- 1 August 2008
The result is a hybrid metaheuristic algorithm called Archive-Based hYbrid Scatter Search (AbYSS), which follows the scatter search structure but uses mutation and crossover operators from evolutionary algorithms, which outperforms the other two algorithms as regards the diversity of the solutions.
The jMetal framework for multi-objective optimization: Design and architecture
- J. Durillo, Antonio J. Nebro, E. Alba
- Computer ScienceIEEE Congress on Evolutionary Computation
- 18 July 2010
The design issues underlying jMetal are described, focusing mainly on its internal architecture, with the aim of offering a comprehensive view of its main features to interested researchers.
Multi-objective workflow scheduling in Amazon EC2
MOHEFT, a Pareto-based list scheduling heuristic that provides the user with a set of tradeoff optimal solutions from which the one that better suits the user requirements can be manually selected, is analysed.
SMPSO : A New PSO Metaheuristic for Multi-objective Optimization
In this work we present a new multi-objective particle swarm optimization algorithm (PSO) characterized by the use of a strategy to limit the velocity of the particles. In this way, the…
jMetal: a Java Framework for Developing Multi-Objective Optimization Metaheuristics
- J. Durillo, Antonio J. Nebro, F. Luna, B. Dorronsoro, E. Alba, Campus de Teatinos
- Computer Science
jMetal provides a rich set of classes which can be used as the building blocks of multi-objective metaheuristics; thus, taking advantage of code-reusing, the algorithms share the same base components, such as implementations of genetic operators and density estimators, so making the fair comparison of different meta heuristics for MOPs possible.
Multi-Objective Particle Swarm Optimizers: An Experimental Comparison
- J. Durillo, J. García-Nieto, Antonio J. Nebro, C. C. Coello, F. Luna, E. Alba
- Computer ScienceEMO
- 21 April 2009
A new MOPSO algorithm is proposed, called SMPSO, characterized by including a velocity constraint mechanism, obtaining promising results where the rest perform inadequately.
MOHEFT: A multi-objective list-based method for workflow scheduling
- J. Durillo, H. M. Fard, R. Prodan
- Computer Science4th IEEE International Conference on Cloud…
- 3 December 2012
A new Pareto-based list scheduling heuristic that provides the user with a set of tradeoff optimal solutions from where the one that better suits the user requirements can be manually selected.