An improved genetic algorithm based on the shortest path problem

The problem of dynamic stochastic shortest path is NP-hard. The transportation network of the city is dynamic and stochastic, the optimal problem of path is widely used in the fields of transportation, communication and computer network. The paper investigates the shortest path problem based on the genetic algorithm principle, an improved self adaptive genetic algorithm is proposed by encoding the chromosomal mode. We improved genetic algorithm by adjusting the encoding parameters. The experiments indicate that the improved genetic algorithm DRSP-GA could obtain the better solutions which adapt to new transportation rapidly in global optimization than A∗ algorithm and Dijkstra algorithm in the shortest path problem.

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