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 428 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. Brandão, Martim; Jirotka, Marina; Webb, Helena; Luff, Paul: Fair navigation planning: a resource for characterizing and designing fairness in mobile robots (2020)
  4. Carvalho, Iago A.; Ribeiro, Marco A.: An exact approach for the minimum-cost bounded-error calibration tree problem (2020)
  5. Drake, John H.; Starkey, Andrew; Owusu, Gilbert; Burke, Edmund K.: Multiobjective evolutionary algorithms for strategic deployment of resources in operational units (2020)
  6. Raimundo, Marcos M.; Ferreira, Paulo A. V.; Von Zuben, Fernando J.: An extension of the non-inferior set estimation algorithm for many objectives (2020)
  7. 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)
  8. Babazadeh, Hossein; Esfahanipour, Akbar: A novel multi period mean-VaR portfolio optimization model considering practical constraints and transaction cost (2019)
  9. Bahri, Oumayma; Benamor, Nahla; Talbi, El-Ghazali: Possibilistic framework for multi-objective optimization under uncertainty (2019)
  10. Chen, Chen; Wei, Yu: Robust multiobjective portfolio optimization: a set order relations approach (2019)
  11. 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)
  12. 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)
  13. 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)
  14. Lin, Wu; Lin, Qiuzhen; Zhu, Zexuan; Li, Jianqiang; Chen, Jianyong; Ming, Zhong: Evolutionary search with multiple utopian reference points in decomposition-based multiobjective optimization (2019)
  15. Palomo-Martínez, Pamela J.; Salazar-Aguilar, M. Angélica: The bi-objective traveling purchaser problem with deliveries (2019)
  16. Wang, Yechuang; Cui, Zhihua; Li, Wuchao: A novel coupling algorithm based on glowworm swarm optimization and bacterial foraging algorithm for solving multi-objective optimization problems (2019)
  17. Zhou, Yuren; He, Xiaoyu; Xiang, Yi; Cai, Shaowei: A set of new multi- and many-objective test problems for continuous optimization and a comprehensive experimental evaluation (2019)
  18. Al-Dujaili, Abdullah; Suresh, S.: Multi-objective simultaneous optimistic optimization (2018)
  19. Askar, S. S.; Abouhawwash, M.: Quantity and price competition in a differentiated triopoly: static and dynamic investigations (2018)
  20. Barbosa, Paulo Alberto Melo; Pinheiro, Plácido Rogério; de Vasconcelos Silveira, Francisca Raquel: Towards the verbal decision analysis paradigm for implementable prioritization of software requirements (2018)

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