SPEA2

SPEA2 - The Strength Pareto Evolutionary Algorithm 2: SPEA2 in an elitist multiobjective evolutionary algorithm. It is an improved version of the Strength Pareto EA (SPEA) and incorporates a fine-grained fitness assignment strategy, a density estimation technique, and an enhanced archive truncation method. SPEA2 operates with a population (archive) of fixed size, from which promising candidated are drawn as parents of the next generation. The resulting offspring then compete with the old ones for inclusion in the population


References in zbMATH (referenced in 314 articles )

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  1. Feliot, Paul; Bect, Julien; Vazquez, Emmanuel: A Bayesian approach to constrained single- and multi-objective optimization (2017)
  2. Kukkonen, Saku; Coello Coello, Carlos A.: Generalized differential evolution for numerical and evolutionary optimization (2017)
  3. Wang, Hao; Ren, Yiyi; Deutz, André; Emmerich, Michael: On steering dominated points in hypervolume indicator gradient ascent for bi-objective optimization (2017)
  4. Karasakal, Esra; Silav, Ahmet: A multi-objective genetic algorithm for a bi-objective facility location problem with partial coverage (2016)
  5. Lei, Hongtao; Wang, Rui; Laporte, Gilbert: Solving a multi-objective dynamic stochastic districting and routing problem with a co-evolutionary algorithm (2016)
  6. Lin, Jianhua; Liu, Min; Hao, Jinghua; Jiang, Shenglong: A multi-objective optimization approach for integrated production planning under interval uncertainties in the steel industry (2016)
  7. Martínez-Frutos, Jesús; Herrero-Pérez, David: Kriging-based infill sampling criterion for constraint handling in multi-objective optimization (2016)
  8. Rohaninejad, Mohammad; Sahraeian, Rashed; Nouri, Behdin Vahedi: Multi-objective optimization of integrated lot-sizing and scheduling problem in flexible job shops (2016)
  9. Schlünz, E.B.; Bokov, P.M.; van Vuuren, J.H.: A comparative study on multiobjective metaheuristics for solving constrained in-core fuel management optimisation problems (2016)
  10. Arrondo, Aránzazu Gila; Redondo, Juana L.; Fernández, José; Ortigosa, Pilar M.: Parallelization of a non-linear multi-objective optimization algorithm: application to a location problem (2015)
  11. Caballero, Rafael; Hernández-Díaz, Alfredo G.; Laguna, Manuel; Molina, Julián: Cross entropy for multiobjective combinatorial optimization problems with linear relaxations (2015)
  12. Duarte, Abraham; Pantrigo, Juan J.; Pardo, Eduardo G.; Mladenovic, Nenad: Multi-objective variable neighborhood search: an application to combinatorial optimization problems (2015)
  13. Hidalgo, Ieda G.; de Barros, Regiane S.; Fernandes, Jéssica P.T.; Estrócio, João Paulo F.; Correia, Paulo B.: Metaheuristic approaches for hydropower system scheduling (2015)
  14. Karshenas, Hossein; Bielza, Concha; Larrañaga, Pedro: Interval-based ranking in noisy evolutionary multi-objective optimization (2015)
  15. Lin, Qiuzhen; Zhu, Qingling; Huang, Peizhi; Chen, Jianyong; Ming, Zhong; Yu, Jianping: A novel hybrid multi-objective immune algorithm with adaptive differential evolution (2015)
  16. Liu, Linzhong; Mu, Haibo; Yang, Juhua: Generic constraints handling techniques in constrained multi-criteria optimization and its application (2015)
  17. Michalak, Krzysztof: Using an outward selective pressure for improving the search quality of the MOEA/D algorithm (2015)
  18. Mladineo, Marko; Veža, Ivica; Gjeldum, Nikola: Single-objective and multi-objective optimization using the HUMANT algorithm (2015)
  19. Ortigosa, P.M.; Hendrix, E.M.T.; Redondo, J.L.: On heuristic bi-criterion methods for semi-obnoxious facility location (2015)
  20. Redondo, Juana L.; Fernández, José; Domingo Álvarez Hervás, José; Gila Arrondo, Aránzazu; Ortigosa, Pilar M.: Approximating the Pareto-front of a planar bi-objective competitive facility location and design problem (2015)

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Further publications can be found at: http://www.tik.ee.ethz.ch/pisa/?page=bugs.php