非线性多目标优化的简单精确障碍-惩罚函数的收敛性

A. Compaoré, K. Somé, J. Poda
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引用次数: 0

摘要

本文提出了一种新的障碍处罚技术的推广。最初的设计是针对不等式约束下的非线性单目标优化问题,现在我们将其转化为求解不等式约束下的非线性多目标优化问题。首先,我们为这一扩展提供了理论基础。其次,给出了新方法求解Pareto最优解的收敛结果。研究结果表明,对于具有不等式约束的多目标优化问题的Pareto最优解的确定,新的惩罚方法具有较好的收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CONVERGENCE OF THE SIMPLE EXACT BARRIER-PENALTY FUNCTION FOR NONLIEAR MULTIOBJECTIVE OPTIMIZATION
In this paper, an extension of the new barrier penalty technical is proposed. Initially, design for nonlinear single-objective optimization with inequality constraints, we have transformed it for solving nonlinear multiobjective optimization problems with inequality constraints. First, we have provided the theoretical foundations for this extension. Secondly, we have stated convergence results of our new method to obtain Pareto optimal solutions. This work shows that the new penalty technique converges well for the determination of Pareto optimal solutions of a multiobjective optimization problems with inequality constraints.
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