Empirical and analytical study of many-objective optimization problems: analysing distribution of nondominated solutions and population size for scalability of randomized heuristics

Author:

Joshi Ramprasad,Deshpande Bharat

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization,General Computer Science

Reference41 articles.

1. Aguirre H, Tanaka K (2005a) Random bit climbers on multiobjective MNK-landscapes: effects of memory and population climbing. IEICE Trans Fundam Electron Commun Comput Sci E 88A(1):334–345

2. Aguirre H, Tanaka K (2005b) Selection, drift, recombination, and mutation in multiobjective evolutionary algorithms on scalable MNK-landscapes. In: Coello Coello CA, Hernández Aguirre A, Zitzler E (eds) Evolutionary multi-criterion optimization, 3rd edn. International conference, EMO 2005. Lecture Notes in Computer Science, vol 3410. Springer, Guanajuato, pp 355–369

3. Aguirre H, Tanaka K (2010) A hybrid selection strategy using scalarization and adaptive $$\epsilon $$ ϵ -ranking for many-objective optimization. Trans Jpn Soc Evol Comput 1(1):65–78 (2010)

4. Aguirre HE, Tanaka K (2004a) Effects of elitism and population climbing on multiobjective MNK-landscapes. In: 2004 Congress on evolutionary computation (CEC’2004), vol 1. IEEE Service Center, Portland, pp 449–456

5. Aguirre HE, Tanaka K (2004b) Insights on properties of multiobjective MNK-landscapes. In: 2004 Congress on evolutionary computation (CEC’2004), vol 1. IEEE Service Center, Portland, pp 196–203

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