Trust-region algorithm based local search for multi-objective optimization

A. El-sawy, Z. M. Hendawy, M. El-Shorbagy
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引用次数: 5

Abstract

In this paper, a new algorithm is proposed to solve multi-objective optimization problems (MOOPs) through applying the trust-region (TR) method based local search (LS) techniques; where the MOOP converting to a single objective optimization problem (SOOP) by using reference point method. In the proposed algorithm, for each reference point the TR algorithm for solving a SOOP is used to obtain a point on the Pareto frontier. In addition a LS method is used, in order to find more points on the Pareto frontier. The algorithm is coded in MATLAB 7.2 and the simulations are run on a Pentium 4 CPU 900 MHz with 512 MB memory capacity. The numerical results show that the proposed method is feasible, and illustrate the ability of finding an approximation of Pareto optimal set.
基于信任域算法的局部搜索多目标优化
本文提出了一种基于局部搜索(LS)技术的信任域(TR)方法求解多目标优化问题的新算法;其中,利用参考点法将MOOP问题转化为单目标优化问题(SOOP)。在该算法中,对于每个参考点,采用求解SOOP的TR算法获得Pareto边界上的一个点。此外,为了在Pareto边界上找到更多的点,还使用了LS方法。该算法用MATLAB 7.2编写,仿真运行在Pentium 4处理器900 MHz、512mb内存上。数值计算结果表明,该方法是可行的,并说明该方法具有寻找Pareto最优集近似的能力。
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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