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首页> 外文期刊>Journal of Taibah University for Science >Generation of Pareto optimal solutions for multi-objective optimization problems via a reduced interior-point algorithm
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Generation of Pareto optimal solutions for multi-objective optimization problems via a reduced interior-point algorithm

机译:通过简化的内点算法生成多目标优化问题的帕累托最优解

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In this paper, a reduced interior-point (RIP) algorithm is introduced to generate a Pareto optimal front for multi-objective constrained optimization (MOCP) problem. A weighted Tchebychev metric approach is used together with achievement scalarizing function approach to convert MOCP problem to a single-objective constrained optimization (SOCO) problem. An active-set technique is used together with a Coleman–Li scaling matrix and a decrease interior-point method to solve SOCO problem. A Matlab implementation of RIP algorithm was used to solve three cases and application. The results showed that the RIP algorithm is promising when compared with well-known algorithms and the computations may be superior relevant for comprehending real-world application problems.
机译:本文介绍了一种简化的内点(RIP)算法来生成多目标约束优化(MOCP)问题的帕累托最优前沿。加权Tchebychev度量方法与成就标量函数方法结合使用,可以将MOCP问题转换为单目标约束优化(SOCO)问题。主动集技术与Coleman-Li缩放矩阵和减少内点法一起使用,可以解决SOCO问题。 RIP算法的Matlab实现解决了三种情况和应用。结果表明,与众所周知的算法相比,RIP算法是有前途的,并且该计算对于理解实际应用问题可能具有更好的相关性。

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