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Experimental Comparison Between Evolutionary Algorithm and Barycenter Heuristic for the Bipartite Drawing Problem | Science Publications

机译:二次绘制问题的进化算法与重心启发式实验比较科学出版物

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> This research investigates the use of intelligent techniques for the bipartite drawing problem (BDP). Due to the combinatorial nature of the solution space, the use of traditional search methods lead to exponential time. Hence, the aim of this paper is to speed up the search time when solving the BDP through the use of Evolutionary Algorithms (EAs) and Barycenter Heuristic (BC). EA is applied on the BDP wherein genetic operators such as crossover and mutation are employed while searching for the best possible solution. The results show that the EA approach guides the search towards optimal solutions and in many instances it outperforms the BC.
机译: >这项研究调查了智能技术在二元图纸问题(BDP)中的使用。由于解空间的组合性质,传统搜索方法的使用导致指数时间。因此,本文的目的是通过使用进化算法(EA)和重心启发式算法(BC)来加快求解BDP时的搜索时间。 EA应用于BDP,其中在寻求最佳解决方案的同时采用了遗传算子(例如交叉和突变)。结果表明,EA方法指导搜索朝着最佳解决方案的方向发展,并且在许多情况下,它的性能优于BC。

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