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ORCIDYoel Tenne
Person information
- affiliation: Ariel University Centre, Israel
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Journal Articles
- 2017
[j10]Yoel Tenne:
Machine-learning in optimization of expensive black-box functions. Int. J. Appl. Math. Comput. Sci. 27(1): 105 (2017)- 2015
- [j9]Yoel Tenne:
Initial sampling methods in metamodel-assisted optimization. Eng. Comput. 31(4): 661-680 (2015) - 2013
- [j8]Yoel Tenne:
An Analysis of the Impact of the Initial Sample on Evolutionary Metamodel-Assisted Optimization. Appl. Artif. Intell. 27(8): 669-699 (2013) - [j7]Yoel Tenne:
An Optimization Algorithm Employing Multiple Metamodels and Optimizers. Int. J. Autom. Comput. 10(3): 227-241 (2013) - [j6]Yoel Tenne:
An algorithm for computationally expensive engineering optimization problems. Int. J. Gen. Syst. 42(5): 458-488 (2013) - 2012
- [j5]Yoel Tenne:
A computational intelligence algorithm for simulation-driven optimization problems. Adv. Eng. Softw. 47(1): 62-71 (2012) - [j4]Yoel Tenne, Kazuhiro Izui
, Shinji Nishiwaki:
A model-adaptive evolutionary algorithm for optimization. Artif. Life Robotics 16(4): 546-550 (2012) - [j3]Yoel Tenne:
A computational intelligence algorithm for expensive engineering optimization problems. Eng. Appl. Artif. Intell. 25(5): 1009-1021 (2012) - [j2]Yoel Tenne, Kazuhiro Izui, Shinji Nishiwaki:
A hybrid model-classifier framework for managing prediction uncertainty in expensive optimisation problems. Int. J. Syst. Sci. 43(7): 1305-1321 (2012) - 2009
- [j1]Yoel Tenne, Steven William Armfield:
A framework for memetic optimization using variable global and local surrogate models. Soft Comput. 13(8-9): 781-793 (2009)
Conference and Workshop Papers
- 2023
- [c9]Yoel Tenne:
Path-extrapolation in Evolutionary Algorithms. AIMLR 2023: 6:1-6:6 - 2021
- [c8]Yoel Tenne:
The RBF Hyperparameter in Metamodel-Assisted Evolutionary Search. CECNet 2021: 84-89 - 2016
- [c7]Yoel Tenne:
Classifier-assisted optimization. SETN 2016: 20:1-20:6 - 2011
- [c6]Yoel Tenne, Kazuhiro Izui, Shinji Nishiwaki:
A Classifier-Assisted Framework for Expensive Optimization Problems: A Knowledge-Mining Approach. LION 2011: 161-175 - 2010
- [c5]Yoel Tenne, Kazuhiro Izui, Shinji Nishiwaki:
Dimensionality-reduction frameworks for computationally expensive problems. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c4]Yoel Tenne, Kazuhiro Izui, Shinji Nishiwaki:
Handling Undefined Vectors in Expensive Optimization Problems. EvoApplications (1) 2010: 582-591 - 2008
- [c3]Yoel Tenne, Steven William Armfield:
Metamodel accuracy assessment in evolutionary optimization. IEEE Congress on Evolutionary Computation 2008: 1505-1512 - 2006
- [c2]Yoel Tenne, Steven William Armfield:
A Novel Evolutionary Algorithm for Efficient Minimization of Expensive Black-box Functions with Assisted-Modelling. IEEE Congress on Evolutionary Computation 2006: 3219-3226 - 2005
- [c1]Yoel Tenne, Steven William Armfield:
Efficiently minimizing expensive cost functions with a hybrid evolutionary algorithm using clustering and a derivative-free optimizer: preliminary results. Congress on Evolutionary Computation 2005: 1937-1944
Parts in Books or Collections
- 2012
- [p3]Yoel Tenne:
Memetic Algorithms in the Presence of Uncertainties. Handbook of Memetic Algorithms 2012: 219-237 - 2009
- [p2]Yoel Tenne:
A Model-Assisted Memetic Algorithm for Expensive Optimization Problems. Nature-Inspired Algorithms for Optimisation 2009: 133-169 - 2007
- [p1]Yoel Tenne, Steven William Armfield:
A Memetic Algorithm Using a Trust-Region Derivative-Free Optimization with Quadratic Modelling for Optimization of Expensive and Noisy Black-box Functions. Evolutionary Computation in Dynamic and Uncertain Environments 2007: 389-415
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