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 321 articles )

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  1. Aalaei, Amin; Kayvanfar, Vahid; Davoudpour, Hamid: A multi-objective optimization for preemptive identical parallel machines scheduling problem (2017)
  2. Feliot, Paul; Bect, Julien; Vazquez, Emmanuel: A Bayesian approach to constrained single- and multi-objective optimization (2017)
  3. Kukkonen, Saku; Coello Coello, Carlos A.: Generalized differential evolution for numerical and evolutionary optimization (2017)
  4. Redondo, J.L.; Fernández, J.; Ortigosa, P.M.: FEMOEA: a fast and efficient multi-objective evolutionary algorithm (2017)
  5. Wang, Hao; Ren, Yiyi; Deutz, André; Emmerich, Michael: On steering dominated points in hypervolume indicator gradient ascent for bi-objective optimization (2017)
  6. Ye Tian, Ran Cheng, Xingyi Zhang, Yaochu Jin: PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization (2017) arXiv
  7. Yuxin, Zhao; Shenghong, Li; Feng, Jin: Overlapping community detection in complex networks using multi-objective evolutionary algorithm (2017)
  8. Karasakal, Esra; Silav, Ahmet: A multi-objective genetic algorithm for a bi-objective facility location problem with partial coverage (2016)
  9. Lei, Hongtao; Wang, Rui; Laporte, Gilbert: Solving a multi-objective dynamic stochastic districting and routing problem with a co-evolutionary algorithm (2016)
  10. 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)
  11. Martínez-Frutos, Jesús; Herrero-Pérez, David: Kriging-based infill sampling criterion for constraint handling in multi-objective optimization (2016)
  12. Rohaninejad, Mohammad; Sahraeian, Rashed; Nouri, Behdin Vahedi: Multi-objective optimization of integrated lot-sizing and scheduling problem in flexible job shops (2016)
  13. 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)
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  15. Caballero, Rafael; Hernández-Díaz, Alfredo G.; Laguna, Manuel; Molina, Julián: Cross entropy for multiobjective combinatorial optimization problems with linear relaxations (2015)
  16. Duarte, Abraham; Pantrigo, Juan J.; Pardo, Eduardo G.; Mladenovic, Nenad: Multi-objective variable neighborhood search: an application to combinatorial optimization problems (2015)
  17. Fettaka, Salim; Thibault, Jules; Gupta, Yash: A new algorithm using front prediction and NSGA-II for solving two and three-objective optimization problems (2015)
  18. 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)
  19. Karshenas, Hossein; Bielza, Concha; Larrañaga, Pedro: Interval-based ranking in noisy evolutionary multi-objective optimization (2015)
  20. Lin, Qiuzhen; Zhu, Qingling; Huang, Peizhi; Chen, Jianyong; Ming, Zhong; Yu, Jianping: A novel hybrid multi-objective immune algorithm with adaptive differential evolution (2015)

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