粒子群蚁群融合算法的火灾救援路径研究

为获取最优的救援路径，以提高救援的有效性和实时性，文中提出了一种粒子群蚁群融合算法。该算法在分析影响路径选择因素的基础上，运用模糊数学中的层次分析法评定了道路的权重，建立了消防灭火救援模型；使用粒子群算法快速获取次优解，将此次优解作为蚁群算法的初始信息素增量，并将求解出各段路径权重矩阵引入到优化后的蚁群算法状态转移概率的求解模型中来，再利用这种改进后的状态转移规则，且考虑行车速度时变性的基础上求解出模型的最优解。实验结果表明，该方法可以完成最佳救援路径的规划。

The Particle Swarm Optimization Algorithm Merged with Ant Colony Optimization Algorithm of Fire Rescue Way Research

To obtain the optimal relief path, improve the effectiveness of the rescue and the real time,so a particle swarm ant colony fusion algorithm is put forward. The major thinking of the optimization is that on the basis of analyzing the factors influencing the path choice, using the analytic hierarchy process of fuzzy mathematics to evaluate the weight of the road, establish the fire fighting rescue model; Then use the particle swarm algorithm quickly get optimal solution,and take the solution as the initial pheromone increment of ant colony algorithm,put the solved each path weight matrix is introduced into the particle swarm ant colony algorithm to solve the model of state transition probability, then use this improved state transition rules, and consider the traffic speed to obtaine the optimal path of the model.Finally, the experimental results show that this method can accomplish the best relief path planning.