Non parameter-filled function for global optimization
作者：
Highlights：
• Parameter free filled function reduces the difficulties during the computational stage affected by the adjustable parameters.
• The absence of the exponential and logarithmic terms in the filled function can avoid overflow effect during numerical implementation.
• Continuously differentiable parameter free filled function can be minimized more easily.
• Computational performance shows that non parameter-filled function is more efficient compared to the parametric filled functions.
摘要
•Parameter free filled function reduces the difficulties during the computational stage affected by the adjustable parameters.•The absence of the exponential and logarithmic terms in the filled function can avoid overflow effect during numerical implementation.•Continuously differentiable parameter free filled function can be minimized more easily.•Computational performance shows that non parameter-filled function is more efficient compared to the parametric filled functions.
论文关键词：Global minimizer,Unconstrained global optimization,Filled function method,Parameter-free,Nonlinear programming
论文评审过程：Received 12 June 2019, Revised 6 May 2020, Accepted 23 August 2020, Available online 11 September 2020, Version of Record 11 September 2020.
论文官网地址：https://doi.org/10.1016/j.amc.2020.125642
