Estimating the quality of initial populations in multi-objective evolutionary algorithms-Reference-Cited by-同舟云学术

Estimating the quality of initial populations in multi-objective evolutionary algorithms

Published:2022-07-09 Issue: Volume: Page:
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Container-title:Proceedings of the Genetic and Evolutionary Computation Conference Companion
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Author:

Benecke Tobias¹,Mostaghim Sanaz¹

Affiliation:

1. Otto-von-Guericke University, Magdeburg, Germany

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3520304.3528796

Reference13 articles.

1. Thomas Bäck . 1996. Evolutionary Algorithms in Theory and Practice: Evolution Strategies , Evolutionary Programming, Genetic Algorithms . Oxford University Press, Inc. Thomas Bäck. 1996. Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford University Press, Inc.

2. The Impact of Population Size on the Convergence of Multi-objective Evolutionary Algorithms

3. Tracking the Heritage of Genes in Evolutionary Algorithms

4. A Study of the Parallelization of a Coevolutionary Multi-objective Evolutionary Algorithm

5. Simulated Binary Crossover for Continuous Search Space;Deb Kalyanmoy;Complex Systems,1995

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1. Effects of Initialization Methods on the Performance of Multi-Objective Evolutionary Algorithms;2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2023-10-01

2. Effects of Including Optimal Solutions into Initial Population on Evolutionary Multiobjective Optimization;Proceedings of the Genetic and Evolutionary Computation Conference;2023-07-12