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 320 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. Redondo, J.L.; Fernández, J.; Ortigosa, P.M.: FEMOEA: a fast and efficient multi-objective evolutionary algorithm (2017)
  4. Wang, Hao; Ren, Yiyi; Deutz, André; Emmerich, Michael: On steering dominated points in hypervolume indicator gradient ascent for bi-objective optimization (2017)
  5. Ye Tian, Ran Cheng, Xingyi Zhang, Yaochu Jin: PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization (2017) arXiv
  6. Yuxin, Zhao; Shenghong, Li; Feng, Jin: Overlapping community detection in complex networks using multi-objective evolutionary algorithm (2017)
  7. Karasakal, Esra; Silav, Ahmet: A multi-objective genetic algorithm for a bi-objective facility location problem with partial coverage (2016)
  8. Lei, Hongtao; Wang, Rui; Laporte, Gilbert: Solving a multi-objective dynamic stochastic districting and routing problem with a co-evolutionary algorithm (2016)
  9. 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)
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  18. Karshenas, Hossein; Bielza, Concha; Larrañaga, Pedro: Interval-based ranking in noisy evolutionary multi-objective optimization (2015)
  19. Lin, Qiuzhen; Zhu, Qingling; Huang, Peizhi; Chen, Jianyong; Ming, Zhong; Yu, Jianping: A novel hybrid multi-objective immune algorithm with adaptive differential evolution (2015)
  20. Liu, Linzhong; Mu, Haibo; Yang, Juhua: Generic constraints handling techniques in constrained multi-criteria optimization and its application (2015)

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