An improved proximal method with quasi-distance for nonconvex multiobjective optimization problem
Saved in:
| Title: | An improved proximal method with quasi-distance for nonconvex multiobjective optimization problem |
|---|---|
| Authors: | Fouzia Amir, Ali Farajzadeh, Jehad Alzabut |
| Source: | Journal of Applied Analysis. 28:333-340 |
| Publisher Information: | Walter de Gruyter GmbH, 2022. |
| Publication Year: | 2022 |
| Subject Terms: | 0211 other engineering and technologies, 02 engineering and technology |
| Description: | Multiobjective optimization is the optimization with several conflicting objective functions. However, it is generally tough to find an optimal solution that satisfies all objectives from a mathematical frame of reference. The main objective of this article is to present an improved proximal method involving quasi-distance for constrained multiobjective optimization problems under the locally Lipschitz condition of the cost function. An instigation to study the proximal method with quasi distances is due to its widespread applications of the quasi distances in computer theory. To study the convergence result, Fritz John’s necessary optimality condition for weak Pareto solution is used. The suitable conditions to guarantee that the cluster points of the generated sequences are Pareto–Clarke critical points are provided. |
| Document Type: | Article |
| Language: | English |
| ISSN: | 1869-6082 1425-6908 |
| DOI: | 10.1515/jaa-2021-2074 |
| Accession Number: | edsair.doi...........e524368b6535f40b15f5d99d4699a28c |
| Database: | OpenAIRE |
Full Text Finder 
Nájsť tento článok vo Web of Science | Abstract: | Multiobjective optimization is the optimization with several conflicting objective functions. However, it is generally tough to find an optimal solution that satisfies all objectives from a mathematical frame of reference. The main objective of this article is to present an improved proximal method involving quasi-distance for constrained multiobjective optimization problems under the locally Lipschitz condition of the cost function. An instigation to study the proximal method with quasi distances is due to its widespread applications of the quasi distances in computer theory. To study the convergence result, Fritz John’s necessary optimality condition for weak Pareto solution is used. The suitable conditions to guarantee that the cluster points of the generated sequences are Pareto–Clarke critical points are provided. |
|---|---|
| ISSN: | 18696082 14256908 |
| DOI: | 10.1515/jaa-2021-2074 |