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Filled function method that avoids minimizing the objective function again
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DOI：10.1080/02331934.2025.2577808.png)
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Abstract
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Filled function algorithm is an effective method for global optimization problems by keeping jumping out of the local minimizer until the global one. The traditional filled function approach goes by minimizing filled function and objective function alternately to find a better local minimizer. Motivated by this, we improve the previous definition of filled function and construct a novel filled function. The proposed filled function does not contain exponential terms, logarithmic terms and parameters that need to be adjusted, and more importantly its minimizers are the better minimizers of the objective function than the current one. The objective function only needs to be minimized once in the proposed corresponding filled function algorithm, which breaks the situation of minimizing filled function and objective function alternately, effectively reduces the number of local optimization and speeds up the process of global optimization. Numerical experiments show that the algorithm is feasible and effective.
Keywords:
Filled function
global optimization
global minimizer
local minimizer
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