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 441 articles )

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  1. Abouhawwash, Mohamed; Jameel, Mohammed; Deb, Kalyanmoy: A smooth proximity measure for optimality in multi-objective optimization using Benson’s method (2020)
  2. Alcaraz, Javier; Landete, Mercedes; Monge, Juan F.; Sainz-Pardo, José L.: Multi-objective evolutionary algorithms for a reliability location problem (2020)
  3. Aravind Krishnamoorthy, Ankit Mishra, Deepak Kamal, Sungwook Hong, Ken-ichi Nomura, Subodh Tiwari, Aiichiro Nakano, Rajiv Kalia, Rampi Ramprasad, Priya Vashishta: EZFF: Python Library for Multi-Objective Parameterization and Uncertainty Quantification of Interatomic Forcefields for Molecular Dynamics (2020) arXiv
  4. Brandão, Martim; Jirotka, Marina; Webb, Helena; Luff, Paul: Fair navigation planning: a resource for characterizing and designing fairness in mobile robots (2020)
  5. Carvalho, Iago A.; Ribeiro, Marco A.: An exact approach for the minimum-cost bounded-error calibration tree problem (2020)
  6. Drake, John H.; Starkey, Andrew; Owusu, Gilbert; Burke, Edmund K.: Multiobjective evolutionary algorithms for strategic deployment of resources in operational units (2020)
  7. Liang, Jing; Li, Zhimeng; Qu, Boyang; Yu, Kunjie; Qiao, Kangjia; Ge, Shilei: A knee point based NSGA-II multi-objective evolutionary algorithm (2020)
  8. Raimundo, Marcos M.; Ferreira, Paulo A. V.; Von Zuben, Fernando J.: An extension of the non-inferior set estimation algorithm for many objectives (2020)
  9. Vo-Duy, T.; Duong-Gia, D.; Ho-Huu, V.; Nguyen-Thoi, T.: An effective couple method for reliability-based multi-objective optimization of truss structures with static and dynamic constraints (2020)
  10. Zhang, Weiwei; Zhang, Ningjun; Wan, Hanwen; Huang, Daoying; Wen, Xiaoyu; Meng, Yinghui: Decomposition based differentiate evolution algorithm with niching strategy for multimodal multi-objective optimization (2020)
  11. Babazadeh, Hossein; Esfahanipour, Akbar: A novel multi period mean-VaR portfolio optimization model considering practical constraints and transaction cost (2019)
  12. Bahri, Oumayma; Benamor, Nahla; Talbi, El-Ghazali: Possibilistic framework for multi-objective optimization under uncertainty (2019)
  13. Bai, Hui; Zheng, Jinhua; Yu, Guo; Yang, Shengxiang; Zou, Juan: A Pareto-based many-objective evolutionary algorithm using space partitioning selection and angle-based truncation (2019)
  14. Bao, Chunteng; Xu, Lihong; Goodman, Erik D.: A novel two-archive matching-based algorithm for multi- and many-objective optimization (2019)
  15. Chen, Chen; Wei, Yu: Robust multiobjective portfolio optimization: a set order relations approach (2019)
  16. Gutierrez, Juan Carlos Ticona; Adamatti, Daniela Santini; Bravo, Juan Martin: A new stopping criterion for multi-objective evolutionary algorithms: application in the calibration of a hydrologic model (2019)
  17. Kar, Mohuya B.; Kar, Samarjit; Guo, Sini; Li, Xiang; Majumder, Saibal: A new bi-objective fuzzy portfolio selection model and its solution through evolutionary algorithms (2019)
  18. Khan, Burhan; Hanoun, Samer; Johnstone, Michael; Lim, Chee Peng; Creighton, Douglas; Nahavandi, Saeid: A scalarization-based dominance evolutionary algorithm for many-objective optimization (2019)
  19. Łapa, Krystian: Meta-optimization of multi-objective population-based algorithms using multi-objective performance metrics (2019)
  20. Li, Hao-ran; He, Fa-zhi; Yan, Xiao-hu: IBEA-SVM: an indicator-based evolutionary algorithm based on pre-selection with classification guided by SVM (2019)

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