Multiobjective Optimization
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-41192-7_23
Reference182 articles.
1. Abbass HA, Sarker R, Newton C. PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems. In: Proceedings of IEEE congress on evolutionary computation (CEC), Seoul, South Korea, May 2001. p. 971–978.
2. Abbass HA. The self-adaptive pareto differential evolution algorithm. In: Proceedings of IEEE congress on evolutionary computation (CEC), Honolulu, HI, USA, May 2002. p. 831–836.
3. Agrawal S, Panigrahi BK, Tiwari MK. Multiobjective particle swarm algorithm with fuzzy clustering for electrical power dispatch. IEEE Trans Evol Comput. 2008;12(5):529–41.
4. Asafuddoula M, Ray T, Sarker R. A decomposition-based evolutionary algorithm for many objective optimization. IEEE Trans Evol Comput. 2015;19(3):445–60.
5. Auger A, Bader J, Brockhoff D, Zitzler E. Theory of the hypervolume indicator: optimal $$\mu $$ -distributions and the choice of the reference point. In: Proceedings of the 10th ACM SIGEVO workshop on foundations of genetic algorithms (FOGA), Orlando, FL, USA, Jan 2009. p. 87–102.
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