一种改进的大型图上多条最短路径的优化算法

Hayi Mohamed Yassine, C. Zahira
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引用次数: 4

摘要

在过去的十年中,寻找最短路径的问题是一个组合优化问题,并且在大型图上是一个具有挑战性的任务。本文提出了一种改进的优化遗传算法(IOGA)来解决k条最短路径问题。本文提出了一种基于精确算法(Dijkstra)和元启发式算法(遗传算法- ga)相结合的算法,用于返回大规模路由问题中图上的k条最短最优路径。我们的实证结果表明,该算法优于Dijkstra算法,并且运行速度更快,并且给出了一条或多条路径,而Dijkstra算法只给出了一条路径。
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An Improved optimization Algorithm to Find Multiple Shortest Paths over Large Graph
The problem of finding the shortest path is a combinatorial well-studied optimization problem, this last decade and is a challenging task over large graphs. This article presents an improved optimization Genetic algorithm (IOGA) to solve the k shortest paths problem. Our algorithm based on the combination of the exact algorithm (Dijkstra) and metaheuristic algorithm (Genetic algorithm-GA) is proposed to return the k shortest optimal paths on graph in large-scale routing problems. Our empirical results show that the proposed algorithm surpasses and runs faster than Dijkstra’s algorithm and gives one or more paths,, while Dijkstra gives only one path.
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