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A new transgenetic approach for the biobjective spanning tree problem

机译:双目标生成树问题的一种新的转基因方法

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This paper addresses a new transgenetic approach to the biobjective spanning tree, an NP-hard combinatorial optimization problem which can model different real applications on network design. The metaheuristic is inspired on endosymbiosis and horizontal gene transfer, two main evolutionary forces. The proposed algorithm is applied to 78 instances with different structures. The results concerning the quality of the approximation sets obtained with the proposed approach are compared to others previously published in the literature with basis on a Pareto compliant quality indicator. Comparisons regarding processing times are also reported. Statistical tests show that the proposed approach is comparable with the algorithms presented in the literature, outperforming them in solution quality for most instances.
机译:本文针对双目标生成树提出了一种新的转基因方法,这是一种NP硬组合优化问题,可以对网络设计中的不同实际应用进行建模。元启发法的灵感来自于内共生和水平基因转移这两种主要的进化力。该算法适用于结构不同的78个实例。在符合帕累托标准的质量指标的基础上,将与通过提议的方法获得的近似集的质量有关的结果与先前在文献中发表的其他结果进行了比较。还报告了有关处理时间的比较。统计测试表明,所提出的方法与文献中提出的算法具有可比性,在大多数情况下其解决方案质量都优于它们。

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