EVOLUTIONARY MULTITASKING: A NEW OPTIMIZATION TECHNIQUE
DOI:
https://doi.org/10.37569/DalatUniversity.8.3.428(2018)Keywords:
Evolutionary Algorithms, Evolutionary Multitasking.Abstract
In the last decades, evolutionary algorithms (EAs) have been successfully applied to solve various optimization problems in science and technology. These issues are usually categorized into two groups: i) Single-objective optimization (SOO), where each point in the search space of the problem is mapped to a target value scalar; and ii) Multi-objective optimization (MOO), where each point in the search space of the problem is mapped to a target vector. In this paper, we will introduce a completely new kind of third-party evolutionary multitasking, which allows simultaneous optimization of different optimization problems on a single population and is called multifactorial optimization (MFO).Downloads
References
Back, T., Hammel, U., & Schwefel, H. P. (1997). Evolutionary computation: Comments on the history and current state. IEEE Transactions on Evolutionary Computation, 1(1), 3-17.
Cloninger, C. R., Rice, J., & Reich, T. (1979). Multifactorial inheritance with cultural transmission and assortative mating. II. A general model of combined polygenic and cultural inheritance. American Journal of Human Genetics, 31(2), 176-198.
Coello, C. A. C. (2006). Evolutionary multi-objective optimization: A historical view of the field. IEEE Computational Intelligence Magazine,1(1), 28-36.
Fonseca, C. M., & Fleming, P. J. (2007). An overview of evolutionary algorithms in multi-objective optimization. Evolution Computing, 3(1), 1-6.
Gupta, E., Ong, Y. S., & Feng, L. (2017). Multifactorial evolution: Towards evolutionary multitasking. IEEE Transactions on Evolutionary Computation, 20(3), 343-357.
Rice, J., Cloninger, C. R., & Reich, T. (1978). Multifactorial inheritance with cultural transmission and assortative mating. I. Description and basic properties of the unitary models. American Journal of Human Genetics, 30(6), 618-643.
Tayarani, N. M. H., & Bennett, P. A. (2013). On the landscape of combinatorial optimization problems. IEEE Transactions on Evolutionary Computation, 18(3), 420-434.
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Copyright (c) 2018 Lại Thị Nhung, Nguyễn Thị Hòa, Phạm Văn Hạnh, Lê Đăng Nguyên, Lê Trọng Vĩnh
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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