Research on transportation optimal path planning based on improved ant colony algorithm

In this paper, an improved ant colony algorithm is proposed to solve the transportation optimal path problem. The algorithm can quickly find the optimal path by improving heuristic function, pheromone and neighbourhood-search. Experimental simulation shows that the improved ant colony algorithm proposed in this paper has certain advantages over genetic algorithm and ant colony algorithm. It not only obtains the minimum value of the optimal path length, but also has the fastest convergence speed, which effectively solves the problem of optimal transportation path planning. The improved algorithm effectively accelerates the transportation speed, shortens the transportation time and saves the transportation cost.