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Solving Stochastic Path Problem: Particle Swarm Optimization Approach

机译:解决随机路径问题:粒子群优化方法

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An stochastic version of the classical shortest path problem whereby for each node of a graph, a probability distribution over the set of successor nodes must be chosen so as to reach a certain destination node with minimum expected cost. In this paper, we propose a new algorithm based on Particle Swarm Optimization (PSO) for solving Stochastic Shortest Path Problem (SSPP). The comparison of our algorithm with other algorithms indicates that its performance is suitable even by the less number of iterations.
机译:经典最短路径问题的随机版本,其中对于图的每个节点,必须选择在后继节点集合上的概率分布,以便以最小的预期成本到达某个目标节点。在本文中,我们提出了一种基于粒子群优化(PSO)的新算法来解决随机最短路径问题(SSPP)。我们的算法与其他算法的比较表明,即使迭代次数较少,其性能也很合适。

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