The Strategic Random Search (SRS) algorithm

Versione 1.0.3 (62,7 KB) da Haoshan Wei
The Strategic Random Search (SRS) is a new global optimization algorithm to solve unconstrained single-objective optimization problems.
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Aggiornato 2 nov 2021

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The Strategic Random Search (SRS) algorithm is a new global optimization algorithm to solve unconstrained single-objective optimization problems.
Contains a total of 3 programs ("SRS.m", "Example.m" and "Compare.m") and 1 dataset ("DataPE.mat"):
(1) "SRS.m" is the main program of the SRS algorithm, and the specific parameters of the algorithm are given.
(2) "Example.m" gives an example of the use of the SRS algorithm for reference.
(3) "Compare.m" compares the convergence of the four algorithms (SRS, SCE-UA, GA, PSO) in a specific situation on the hydrological model GR4J, and gives the calling methods of the four algorithms and the differences in the results.
(4) "DataPE.mat" is the supporting data set of "Compare.m".

Cita come

Haoshan Wei (2024). The Strategic Random Search (SRS) algorithm (https://www.mathworks.com/matlabcentral/fileexchange/101373-the-strategic-random-search-srs-algorithm), MATLAB Central File Exchange. Recuperato .

Compatibilità della release di MATLAB
Creato con R2018b
Compatibile con qualsiasi release
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Ispirato da: Shuffled Complex Evolution (SCE-UA) Method

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Versione Pubblicato Note della release
1.0.3

The annotations of the algorithm are slightly modified.
1.0.2

The annotations of the algorithm are slightly modified.
1.0.1

Modified the description of the algorithm
1.0.0