Abstract
Finding a constraint shortest path which passes through a set of specified vertices is very important for many research areas, such as intelligent transportation systems, emergency rescue, and military planning. In this paper, we propose an efficient genetic algorithm for solving the constraint shortest path problem. Firstly, the Dijkstra algorithm is used to calculate the shortest distance between any two specified vertices. The optimal solution change from the original problem into the Hamilton path problem with the specified vertices. Because the number of specified vertices is much less than the number of vertices for the whole road network, the search space would be reduced exponentially. Secondly, the genetic algorithm is adopted to search for the optimal solution of the Hamilton path problem. Thirdly our algorithm should detect and eliminate the cycle path. Finally, the performance of our algorithm is evaluated by some real-life city road networks and some randomly generated road networks. The computational results show that our algorithm can find the constraint shortest path efficiently and effectively.
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