[1]
Margarita Reyes-Sierra and Carlos A. Coello Coello, Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art, International Journal of Computational Intelligence Research, 2006, 2(3), p.287–308.
DOI: 10.5019/j.ijcir.2006.68
Google Scholar
[2]
C. A. Coello Coello and M. S. Lechuga, MOPSO: A proposal for multiple objective particle swarm optimization, " in Proc. of IEEE World Congress on Computational Intelligence (CEC, 02), 2002, pp.1051-1056.
DOI: 10.1109/cec.2002.1004388
Google Scholar
[3]
X. Hu and R. Eberhart: Multiobjective Optimization Using Dynamic Neighborhood Particle Swarm Optimization, In: Proceedings of the 2002 Congess on Evolutionary Computation, IEEE Press (2002).
DOI: 10.1109/cec.2002.1004494
Google Scholar
[4]
S. Mostaghim and J. Teich, Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO), in: IEEE 2003 Swarm Intelligence Symposium, 2003, pp.26-33.
DOI: 10.1109/sis.2003.1202243
Google Scholar
[5]
Julio E. Alvarez-Benitez, Richard M. Everson and Jonathan E. Fieldsend, A MOPSO Algorithm Based Exclusively on Pareto Dominance, Evolutionary Multi-Criterion Optimization, Lecture Notes in Computer Science, Vol. 3410 (2005), pp.459-473.
DOI: 10.1007/978-3-540-31880-4_32
Google Scholar
[6]
Tapabrata Ray and K.M. Liew, A swarm metaphor for multiobjective design optimization, Engineering optimization, 2002, 34(2), p.141–153.
DOI: 10.1080/03052150210915
Google Scholar
[7]
Carlos A. Coello Coello and Maximino Salazar Lechuga, MOPSO: A proposal for multiple objective particle swarm optimization, In Congress on Evolutionary Computation (CEC'2002), Piscataway, New Jersey, IEEE Service Center, Vol. 2(2002).
DOI: 10.1109/cec.2002.1004388
Google Scholar
[8]
Carlos A. Coello Coello, Gregorio Toscano Pulido, and Maximino Salazar Lechuga, Handling multiple objectives with particle swarm optimization, IEEE Transactions on Evolutionary Computation, 2004, 8(3), p.256–279.
DOI: 10.1109/tevc.2004.826067
Google Scholar
[9]
Thomas Bartz-Beielstein, Philipp Limbourg, Konstantinos E. Parsopoulos, Michael N. Vrahatis, Jorn Mehnen, and Karlheinz Schmitt. Particle swarm optimizers for pareto optimization with enhanced archiving techniques. In Congress on Evolutionary Computation (CEC'2003), Canberra, Australia, IEEE Press, Vol. 3 (2003).
DOI: 10.1109/cec.2003.1299888
Google Scholar
[10]
Juan Carlos, Fuentes Cabrera and Carlos A. Coello Coello, Micro-MOPSO: A Multi-Objective Particle Swarm Optimizer That Uses a Very Small Population Size, Multi-Objective Swarm Intelligent Systems Studies in Computational Intelligence, Vol. 261 (2010).
DOI: 10.1007/978-3-642-05165-4_4
Google Scholar
[11]
Maximino Salazar-Lechuga and Jonathan Rowe, Particle swarm optimization and fitness sharing to solve multi-objective optimization problems, In Congress on Evolutionary Computation (CEC'2005), Edinburgh, Scotland, UK. IEEE Press, 2005, p.1204.
DOI: 10.1109/cec.2005.1554827
Google Scholar
[12]
Stefan Janson and Daniel Merkle, A New Multi-objective Particle Swarm Optimization Algorithm Using Clustering Applied to Automated Docking, Hybrid Metaheuristics Lecture Notes in Computer Science, Vol. 3636 (2005), pp.128-141.
DOI: 10.1007/11546245_12
Google Scholar
[13]
Shih-Yuan Chiu, Tsung-Ying Sun, Sheng-Ta Hsieh and Cheng-Wei Lin, Cross-searching strategy for multi-objective particle swarm optimization, Evolutionary Computation, 2007. CEC 2007. IEEE Congress on Digital Object Identifier: 10. 1109/CEC. 2007. 4424872, p.3135.
DOI: 10.1109/cec.2007.4424872
Google Scholar