Newton iteration with weighted exponential penalty function for solving multi-objective constrained optimization problems

Peng Cheng and Jumat Sulaiman and Khadizah Ghazali and Majid Khan Majahar Ali and Ming Ming Xu (2025) Newton iteration with weighted exponential penalty function for solving multi-objective constrained optimization problems. Journal of Quality Measurement and Analysis, 21 (2). pp. 1-16. ISSN 2600-8602

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Abstract

In this paper, the Newton iterative method and weighted exponential penalty function method for solving multi-objective constrained optimization problems are proposed on the basis of classical optimization methods for mathematical planning. Firstly, according to the characteristics of the objective function, it is transformed into a single-objective constrained optimization problem using variable weight coefficients. Then according to the characteristics of the constraints, the exponential penalty function method is used to transform it into an unconstrained optimization problem. Finally, Newton's method is used to solve the transformed unconstrained optimization problem to obtain the efficient Pareto solution of the original problem. The convergence of the method is included in the paper, and numerical experiments show that our proposed method can obtain a set of effective Pareto solutions corresponding to multi-objective optimization problems in different dimensions.

Item Type: Article
Keyword: Multi-objective constrained optimization; weighting method; exponential penalty function method; Newton's method
Subjects: Q Science > QA Mathematics > QA1-939 Mathematics
Q Science > QC Physics > QC1-999 Physics > QC170-197 Atomic physics. Constitution and properties of matter
Department: FACULTY > Faculty of Science and Natural Resources
Depositing User: ABDULLAH BIN SABUDIN -
Date Deposited: 16 Jul 2025 17:16
Last Modified: 16 Jul 2025 17:16
URI: https://eprints.ums.edu.my/id/eprint/44517

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