HYBRID METHOD BASED ON EXPONENTIAL PENALTY FUNCTION AND MOMA-PLUS METHOD FOR MULTIOBJECTIVE OPTIMIZATION

A. Som, K. Somé, A. Compaoré
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引用次数: 1

Abstract

In this paper, we propose a modified version of the MOMA-plus method to solve multiobjective optimization problems. We use an exponential penalty function instead of the Lagrangian penalty function in the initial version of MOMA-Plus in order to improve the convergence and distribution to the Pareto optimal solutions. The theoretical and numerical results show that this new version improves the quality of the obtained solutions compared to the last version. Six test problems have been successfully resolved, allowing us to highlight the good convergence and good distribution of Pareto optimal solutions.
基于指数罚函数和moma-plus的多目标优化混合方法
在本文中,我们提出了一个修正版本的MOMA-plus方法来解决多目标优化问题。为了提高Pareto最优解的收敛性和分布性,我们在MOMA-Plus的初始版本中使用指数罚函数代替拉格朗日罚函数。理论和数值结果表明,与旧版本相比,新版本提高了解的质量。成功地解决了六个测试问题,使我们能够突出Pareto最优解的良好收敛性和良好分布性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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