Numerical and Evolutionary Optimization 2021
نویسندگان
چکیده
This Special Issue was inspired by the 9th International Workshop on Numerical and Evolutionary Optimization (NEO 2021) held—due to COVID-19 pandemic—as an online-only event from 8 10 September 2021 [...]
منابع مشابه
An Adaptive Evolutionary Algorithm for Numerical Optimization
In this paper, a normalized oating point representation has been used for making it be possible to design biotechnical genetic operators as well as to apply some genetic operators like inversion. To improve the adaptation of evolutionary algorithms and avoid the biases which may exist in some genetic operators, we have designed and applied several kinds of genetic operators with some probabilit...
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A version of Modified Bacterial Foraging Optimization Algorithm to solve Constraints Numerical Optimization is tested. The proposal uses mutation operator, skew mechanism and local search operator. To prove the effectiveness of the mechanism and adaptations proposed, 24 well-known test problems are solved along set experiments. Performance measures are used for validating results obtained by th...
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In the real world, many of the optimization issues are dynamic, uncertain, and complex in which the objective function or constraints can be changed over time. Consequently, the optimum of these issues is changed nonlinearly. Therefore, the optimization algorithms not only should search the global optimum value in the space but also should follow the path of optimal change in dynamic environmen...
متن کاملA Comparative Study of Quantum Evolutionary Algorithm and Particle Swarm Optimization for Numerical Optimization Problems
Quantum evolutionary algorithm (QEA) and particle swarm optimization (PSO) are two different types of intelligent optimization algorithm. Many efforts on these two algorithms have progressed actively in recent years. In this paper, six typical and complex benchmark testing functions are applied to verify their abilities for dealing with numerical optimization problems. The results show that QEA...
متن کاملApplying evolutionary optimization on the airfoil design
In this paper, lift and drag coefficients were numerically investigated using NUMECA software in a set of 4-digit NACA airfoils. Two metamodels based on the evolved group method of data handling (GMDH) type neural networks were then obtained for modeling both lift coefficient (CL) and drag coefficient (CD) with respect to the geometrical design parameters. After using such obtained polynomial n...
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ژورنال
عنوان ژورنال: Mathematical and computational applications
سال: 2023
ISSN: ['1300-686X', '2297-8747']
DOI: https://doi.org/10.3390/mca28030071