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The shortest path optimization based on mutation particle swarm optimization algorithm

机译:基于突变粒子群优化算法的最短路径优化

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The traditional evolutionary algorithm is cannot converge faster to solve the path optimization problems, and the path that is computed is not the shortest path, in allusion to the disadvantage of this algorithm, a mutation particle swarm optimization algorithm is proposed. The algorithm introduces the adaptive mutation strategy, and accelerated the speed to search for the global optimal solution. For seven examples experiment in standard database, the result shows that the algorithm is more efficient..
机译:传统的进化算法不能更快地收敛以解决路径优化问题,并且计算的路径不是该算法的缺点中的最短路径,提出了一种突变粒子群优化算法。该算法介绍了自适应突变策略,加速了寻找全局最优解决方案的速度。对于标准数据库中的七个示例实验,结果表明该算法更有效..

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