# A filled function method for global optimization with inequality constraints

## Abstract

In this paper, we propose a new filled function method for finding a global minimizer of global optimization with inequality constraints. The proposed filled function is a continuously differentiable function with only one parameter. Then, we can use classical local optimization methods to find a better minimizer of the proposed filled function with a few parameter adjustment. The numerical experiments are made and the results show that the proposed filled function method is effective.

- Authors:

- Jinling Institute of Technology, Department of Fundamental Courses and Jiangsu Key Laboratory of Data Science & Smart Software (China)
- Xidian University, School of Computer Science and Technology (China)
- Beifang University for Nationalities, Information and System Science (China)

- Publication Date:

- OSTI Identifier:
- 22769342

- Resource Type:
- Journal Article

- Journal Name:
- Computational and Applied Mathematics

- Additional Journal Information:
- Journal Volume: 37; Journal Issue: 2; Other Information: Copyright (c) 2018 SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0101-8205

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 97 MATHEMATICAL METHODS AND COMPUTING; FUNCTIONS; LIMITING VALUES; OPTIMIZATION

### Citation Formats

```
Lin, Hongwei, Wang, Yuping, Gao, Yuelin, and Wang, Xiaoli.
```*A filled function method for global optimization with inequality constraints*. United States: N. p., 2018.
Web. doi:10.1007/S40314-016-0407-8.

```
Lin, Hongwei, Wang, Yuping, Gao, Yuelin, & Wang, Xiaoli.
```*A filled function method for global optimization with inequality constraints*. United States. doi:10.1007/S40314-016-0407-8.

```
Lin, Hongwei, Wang, Yuping, Gao, Yuelin, and Wang, Xiaoli. Tue .
"A filled function method for global optimization with inequality constraints". United States. doi:10.1007/S40314-016-0407-8.
```

```
@article{osti_22769342,
```

title = {A filled function method for global optimization with inequality constraints},

author = {Lin, Hongwei and Wang, Yuping and Gao, Yuelin and Wang, Xiaoli},

abstractNote = {In this paper, we propose a new filled function method for finding a global minimizer of global optimization with inequality constraints. The proposed filled function is a continuously differentiable function with only one parameter. Then, we can use classical local optimization methods to find a better minimizer of the proposed filled function with a few parameter adjustment. The numerical experiments are made and the results show that the proposed filled function method is effective.},

doi = {10.1007/S40314-016-0407-8},

journal = {Computational and Applied Mathematics},

issn = {0101-8205},

number = 2,

volume = 37,

place = {United States},

year = {2018},

month = {5}

}

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