The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Um método foi desenvolvido para derivar o ótimo global aproximado de uma função objetivo não linear com múltiplos ótimos locais. A função objetivo é expandida em uma equação de coeficiente de onda linear, de modo que o problema de maximizar a função objetivo é reduzido ao de maximizar uma função quadrática em relação aos coeficientes de onda. Como uma função de onda expressa pelos coeficientes de onda é usada no algoritmo para maximizar a função quadrática, o algoritmo é equivalente a um algoritmo de busca completa, ou seja, um algoritmo que busca em paralelo o ótimo global em todo o domínio de definição. Portanto, o ótimo global é sempre derivado. O método foi avaliado para diversas funções objetivo, e a simulação computacional mostrou que sempre pode ser obtida uma boa aproximação do ótimo global para cada função objetivo.
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Hideki SATOH, "Global Nonlinear Optimization Based on Wave Function and Wave Coefficient Equation" in IEICE TRANSACTIONS on Fundamentals,
vol. E93-A, no. 1, pp. 291-301, January 2010, doi: 10.1587/transfun.E93.A.291.
Abstract: A method was developed for deriving the approximate global optimum of a nonlinear objective function with multiple local optimums. The objective function is expanded into a linear wave coefficient equation, so the problem of maximizing the objective function is reduced to that of maximizing a quadratic function with respect to the wave coefficients. Because a wave function expressed by the wave coefficients is used in the algorithm for maximizing the quadratic function, the algorithm is equivalent to a full search algorithm, i.e., one that searches in parallel for the global optimum in the whole domain of definition. Therefore, the global optimum is always derived. The method was evaluated for various objective functions, and computer simulation showed that a good approximation of the global optimum for each objective function can always be obtained.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E93.A.291/_p
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@ARTICLE{e93-a_1_291,
author={Hideki SATOH, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Global Nonlinear Optimization Based on Wave Function and Wave Coefficient Equation},
year={2010},
volume={E93-A},
number={1},
pages={291-301},
abstract={A method was developed for deriving the approximate global optimum of a nonlinear objective function with multiple local optimums. The objective function is expanded into a linear wave coefficient equation, so the problem of maximizing the objective function is reduced to that of maximizing a quadratic function with respect to the wave coefficients. Because a wave function expressed by the wave coefficients is used in the algorithm for maximizing the quadratic function, the algorithm is equivalent to a full search algorithm, i.e., one that searches in parallel for the global optimum in the whole domain of definition. Therefore, the global optimum is always derived. The method was evaluated for various objective functions, and computer simulation showed that a good approximation of the global optimum for each objective function can always be obtained.},
keywords={},
doi={10.1587/transfun.E93.A.291},
ISSN={1745-1337},
month={January},}
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TY - JOUR
TI - Global Nonlinear Optimization Based on Wave Function and Wave Coefficient Equation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 291
EP - 301
AU - Hideki SATOH
PY - 2010
DO - 10.1587/transfun.E93.A.291
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E93-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2010
AB - A method was developed for deriving the approximate global optimum of a nonlinear objective function with multiple local optimums. The objective function is expanded into a linear wave coefficient equation, so the problem of maximizing the objective function is reduced to that of maximizing a quadratic function with respect to the wave coefficients. Because a wave function expressed by the wave coefficients is used in the algorithm for maximizing the quadratic function, the algorithm is equivalent to a full search algorithm, i.e., one that searches in parallel for the global optimum in the whole domain of definition. Therefore, the global optimum is always derived. The method was evaluated for various objective functions, and computer simulation showed that a good approximation of the global optimum for each objective function can always be obtained.
ER -