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Particle swarm optimization for the multi level capacitated minimum spanning tree

机译:多级容量最小生成树的粒子群优化

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In the presented study Particle Swarm Optimization will be applied on an instance of the Multi Level Capacitated Minimum Spanning Tree Problem. Specifically a diversity preservation global variant of the PSO meta-heuristic will be presented. The particular PSO variant includes Gaussian mutation to avoid premature convergence and alternative selection of the flight guide per particle. Obtained results are compared with corresponding evolutionary approaches. Potential tree solutions are encoded/decoded using Network Random Keys. A real world network design case is introduced.
机译:在提出的研究中,粒子群优化将应用于多级容量最小生成树问题的实例。具体来说,将介绍PSO元启发式算法的多样性保留全局变体。特定的PSO变体包括高斯突变,以避免过早收敛以及每个粒子的飞行指南的替代选择。将获得的结果与相应的进化方法进行比较。潜在树解决方案使用网络随机密钥进行编码/解码。介绍了一个现实世界的网络设计案例。

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