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Approximations on minimum weight pseudo-triangulation problem using ant colony optimization

机译:使用蚁群优化的最小权重伪三角剖分逼近

摘要

In this work, we consider the Minimum Weight Pseudo-Triangulation (MWPT) problem of a given set of n points in the plane. Globally optimal pseudo-triangulations with respect to the weight, as optimization criteria, are difficult to be found by deterministic methods, since no polynomial algorithm is known. We show how the Ant Colony Optimization (ACO) metaheuristic can be used to find high quality pseudo-triangulations of minimum weight. We present the experimental and statistical study based on our own set of instances since no reference to benchmarks for these problems were found in the literature. Throughout the experimental evaluation, we appraise the ACO metaheuristic performance for MWPT problem.
机译:在这项工作中,我们考虑了平面中n个给定集合的最小权重伪三角剖分(MWPT)问题。由于没有多项式算法是已知的,因此很难通过确定性方法找到关于权重的全局最优伪三角剖分作为优化标准。我们展示了如何使用蚁群优化(ACO)元启发式算法来找到最小权重的高质量伪三角剖分。由于我们在文献中未找到针对这些问题的基准,因此我们根据自己的实例进行了实验和统计研究。在整个实验评估中,我们评估了MWPT问题的ACO元启发式性能。

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