The Pareto Archived Evolution Strategy (PAES) is a multiobjective optimizer which uses a simple (1+1) local search evolution strategy. Nonetheless, it is capable of finding diverse solutions in the Pareto optimal set because it maintains an archive of nondominated solutions which it exploits to estimate accurately the quality of new candidate solutions. Three versions, (1+1), (1+lambda) and (mu+lambda)-PAES have been developed. Each of these versions has been tested against two well known multiobjective evolutionary algorithms - the Niched Pareto Genetic Algorithm (NPGA) and a nondominated sorting GA (NSGA). Tests were carried out using five test functions (f2-f6) and results have been processed using statistical techniques introduced by Fonseca and Fleming. C code for each of the test functions and the statistical techniques are available below. Please drop me an email if you use any of these resources.

References in zbMATH (referenced in 78 articles )

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  1. Redondo, J.L.; Fernández, J.; Ortigosa, P.M.: FEMOEA: a fast and efficient multi-objective evolutionary algorithm (2017)
  2. Martí, Luis; García, Jesús; Berlanga, Antonio; Molina, José M.: MONEDA: scalable multi-objective optimization with a neural network-based estimation of distribution algorithm (2016)
  3. Liu, Linzhong; Mu, Haibo; Yang, Juhua: Generic constraints handling techniques in constrained multi-criteria optimization and its application (2015)
  4. Shang, Ronghua; Wang, Yuying; Wang, Jia; Jiao, Licheng; Wang, Shuo; Qi, Liping: A multi-population cooperative coevolutionary algorithm for multi-objective capacitated arc routing problem (2014)
  5. Akay, Bahriye: Synchronous and asynchronous Pareto-based multi-objective artificial bee colony algorithms (2013)
  6. Idoumghar, Lhassane; Chérin, Nicolas; Siarry, Patrick; Roche, Robin; Miraoui, Abdellatif: Hybrid ICA-PSO algorithm for continuous optimization (2013)
  7. Ortega, Fernando; Sánchez, José-Luis; Bobadilla, Jesús; Gutiérrez, Abraham: Improving collaborative filtering-based recommender systems results using Pareto dominance (2013) ioport
  8. Zhou, Aimin; Gao, Feng; Zhang, Guixu: A decomposition based estimation of distribution algorithm for multiobjective traveling salesman problems (2013)
  9. Ali, Musrrat; Siarry, Patrick; Pant, Millie: An efficient differential evolution based algorithm for solving multi-objective optimization problems (2012)
  10. Claro, João; Pinho de Sousa, Jorge: A multiobjective metaheuristic for a mean-risk multistage capacity investment problem with process flexibility (2012)
  11. Salazar-Aguilar, M.Angélica; Ríos-Mercado, Roger Z.: Multiobjective scatter search for a commercial territory design problem (2012)
  12. Zhang, Jingling; Wang, Wanliang; Zhao, Yanwei; Cattani, Carlo: Multiobjective quantum evolutionary algorithm for the vehicle routing problem with customer satisfaction (2012)
  13. Zinflou, Arnaud; Gagné, Caroline; Gravel, Marc: GISMOO: A new hybrid genetic/immune strategy for multiple-objective optimization (2012)
  14. Husain, Afzal; Lee, Ki-Don; Kim, Kwang-Yong: Enhanced multi-objective optimization of a dimpled channel through evolutionary algorithms and multiple surrogate methods (2011)
  15. Khorshidi, M.; Soheilypour, M.; Peyro, M.; Atai, A.; Panahi, M.Shariat: Optimal design of four-bar mechanisms using a hybrid multi-objective GA with adaptive local search (2011)
  16. Konak, Abdullah; Smith, Alice E.: Efficient optimization of reliable two-node connected networks: a biobjective approach (2011)
  17. Kruse, Rudolf; Borgelt, Christian; Klawonn, Frank; Moewes, Christian; Ruß, Georg; Steinbrecher, Matthias: Computational intelligence. A methodological introduction to artificial neural nets, evolutionary algorithms, fuzzy systems and Bayes nets (2011)
  18. Li, Minqiang; Liu, Liu; Lin, Dan: A fast steady-state $\varepsilon $-dominance multi-objective evolutionary algorithm (2011)
  19. Shin, Kyoung Seok; Park, Jong-Oh; Kim, Yeo Keun: Multi-objective FMS process planning with various flexibilities using a symbiotic evolutionary algorithm (2011)
  20. Wang, Long; Wang, Tong-guang; Luo, Yuan: Improved non-dominated sorting genetic algorithm (NSGA)-II in multi-objective optimization studies of wind turbine blades (2011)

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