Work

A class of objective filled penalty functions for minimax global optimization problem

Year: 2025

Type: article

Abstract: This research proposes a class of filled objective penalty functions for seeking global optimal solutions to minimax constrained optimization problems. A class of objective penalty functions is constructed to obtain the local optimal solutions. Building upon these local optimal solutions, the article introduces a class of objective penalty functions with filled properties, termed as filled penalty functions. Using these filled penalty functions, our algorithm finds a globally approximate solution in finite steps. The time complexity is also analyzed. Finally, straightforward numerical examples are provided to demonstrate the effectiveness of the proposed algorithm.

Source: Journal of Inequalities and Applications

DOI: 10.1186/s13660-025-03391-7

Authors: Jiahui Tang, Yifan Xu, Wei Wang

Institutions: Shanghai Polytechnic University, Fudan University, East China University of Science and Technology

Language: English

Topic: Advanced Optimization Algorithms Research

Subfield: Numerical Analysis

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,190

OpenAlex ID: W4416225364

FWCI:

Cites: 20

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