Approximate Solution to Multi-Objective Optimization Problems Involving Parameter Uncertainty and Non-Linear Constraints

Citation

Gao, Yufeng and Shi, Xiangqian (2026) Approximate Solution to Multi-Objective Optimization Problems Involving Parameter Uncertainty and Non-Linear Constraints. Journal of Information Science and Engineering, 42 (2). pp. 423-443. ISSN 10162364

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Abstract

Optimization problems are widespread in practical engineering problems and often contain multiple conflicting optimization objectives. Hence the need for multi-objective optimization of engineering problems. The errors arising from the coupling of numerous uncertain information contained in multi-objective optimization problems can impact the accuracy of the system structure. This paper investigates the proposed approximate solution to the multi-objective optimization problem. The given unified non-linear scalarization problem for the multi-objective optimization problem is studied without any convexity condition, and the sufficient and necessary conditions for the proposed approximate solution to the multi-objective optimization problem are investigated. Finally, using the given parametrization, the proposed approximate solution of the multi-objective optimization problem is inscribed by a non-linear scalarization, where the interval range of the objective function can be obtained by performing a Taylor expansion at the midpoint value of the interval of the uncertain variables followed by a natural interval expansion; the interval likelihood model is then invoked to transform the un-certainty constraint function into a deterministic constraint function. The method's effective-ness is better verified by comparing the optimi

Item Type: Article
Uncontrolled Keywords: Multi-objective optimization, proposed approximate solution
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28-70 Management. Industrial Management
Divisions: Faculty of Management (FOM)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 02 Apr 2026 05:41
Last Modified: 02 Apr 2026 05:41
URII: http://shdl.mmu.edu.my/id/eprint/15656

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