基于Petri网与改进A星搜索算法的矿井机车调度优化

为了提高煤矿井下机车调度效率、防止机车碰撞、堵塞,根据井下调度特点建立了机车运行赋时Petri网模型。针对原有启发式A*搜索算法存在的易陷入局部最优的缺点,提出了基于petri网的并发变迁遴选算法,引入变迁并发度概念,与启发式A*搜索算法相结合,得到改进的A*搜索算法。经过改进后算法的回溯计算,得到Petri可达图上的最佳路径,从而得出最优调度策略。根据以上算法进行MATLAB建模,最终仿真结果表明,经过改进的启发式A*搜索算法有效的避免了陷入局部最优解,其计算得出的调度路径及调度策略资源消耗量最少,调度效率较高且未出现机车堵塞碰撞等问题。

Optimization of mine locomotive scheduling based on Petri net and improved A star search algorithm

In order to improve the efficiency of underground locomotive dispatching and prevent locomotive collision and blockage, according to the characteristics of mine scheduling, the time Petri network model of locomotive operation is established. Aiming at the shortcomings of the original heuristic A* search algorithm, which is easy to be trapped in local optimal, a concurrency transition selection algorithm based on petri net is proposed. The concept of transition concurrency is introduced, combined it with heuristic A* search algorithm, the improved A* search algorithm is obtained. After retrospective calculation, the best path on the Petri reachable marking graph is obtained, then the optimal scheduling strategy is obtained. MATLAB modeling was carried out according to the above algorithm, and the final simulation results showed that the improved heuristic A * search algorithm effectively avoids falling into the local optimal solution. The calculated scheduling strategy resource consumption is the least, the scheduling efficiency is high, and there is no locomotive jam collision.