This letter describes a semi-random searching algorithm for global optimization problems which can reduce the number of objective function evaluations significantly via a deterministic criterion and can find a global optimum via a stochastic criterion. The utility of this algorithm is demonstrated by several examples.
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Jin-Qin LU, Takehiko ADACHI, "A Semi-Random Searching Algorithm for Global Optimization Design on Electronic Circuits" in IEICE TRANSACTIONS on Fundamentals,
vol. E74-A, no. 5, pp. 1011-1013, May 1991, doi: .
Abstract: This letter describes a semi-random searching algorithm for global optimization problems which can reduce the number of objective function evaluations significantly via a deterministic criterion and can find a global optimum via a stochastic criterion. The utility of this algorithm is demonstrated by several examples.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e74-a_5_1011/_p
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@ARTICLE{e74-a_5_1011,
author={Jin-Qin LU, Takehiko ADACHI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Semi-Random Searching Algorithm for Global Optimization Design on Electronic Circuits},
year={1991},
volume={E74-A},
number={5},
pages={1011-1013},
abstract={This letter describes a semi-random searching algorithm for global optimization problems which can reduce the number of objective function evaluations significantly via a deterministic criterion and can find a global optimum via a stochastic criterion. The utility of this algorithm is demonstrated by several examples.},
keywords={},
doi={},
ISSN={},
month={May},}
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TY - JOUR
TI - A Semi-Random Searching Algorithm for Global Optimization Design on Electronic Circuits
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1011
EP - 1013
AU - Jin-Qin LU
AU - Takehiko ADACHI
PY - 1991
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E74-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 1991
AB - This letter describes a semi-random searching algorithm for global optimization problems which can reduce the number of objective function evaluations significantly via a deterministic criterion and can find a global optimum via a stochastic criterion. The utility of this algorithm is demonstrated by several examples.
ER -