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A novel non-parameter filled function method for unconstrained global optimization
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DOI：10.1051/ro/2025135.png)
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Abstract
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The filled function is considered to be an effective method for solving global optimization problems. It obtains the global optimal solution of the optimization problem by alternating the two stages of minimization and filling. Firstly, this paper proposes a new parameter-free and continuously differentiable filled function, which does not contain exponential terms and logarithmic terms, and overcomes some shortcomings in the form of the original parameter filled function. Secondly, it is proved that the proposed function satisfies the filled property and some good analytical properties, and the corresponding filled function algorithm is given. Experiments are carried out on some benchmark functions and the application of earthwork allocation problem. Finally, the numerical results show the effectiveness and stability of the algorithm.
Keywords:
Global optimization
filled function
local minimizer
global minimizer
Journal
R
IF:
2.1
Papers:
95
Citations:
0
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Cited Papers
A novel convergent filled function algorithm for multi-dimensional global optimization.png)
Optimization
OptimizationIF0
PREAI
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