基于改进NSGA-Ⅱ算法的消防车辆调度优化

Fire Trucks Scheduling Optimization Based on Improved NSGA-Ⅱ Algorithm

传统多目标优化算法用于消防车调度时存在冲突解及精度较低的限制,为此提出一种改进的NSGA-Ⅱ算法。为解决消防车调度中染色体基因重复出现的问题,对基因进行分组并分配权重,提高种群的适应能力;为使种群朝指定方向收敛,设置目标函数的优先级,从而提高算法的精确度。将改进的NSGA-Ⅱ算法与原算法进行比较分析,并对优化结果进行三维可视化。实验结果表明,改进的NSGA-Ⅱ算法能够得到更加准确的Pareto解集。

Aiming atlimitations of conflict solution and low accuracy of traditional multi-objective optimization algorithm in fire trucks scheduling,an improved NSGA-Ⅱalgorithm is proposed in this paper.In order to solve the problem of duplication of genes in fire trucks scheduling,all genes are grouped and assigned weights,and the adaptive ability of the population is enhanced.In order to make the population converge to the specified direction,the priorities of objective functions are set,leading to an improved accuracy.The improved NSGA-Ⅱalgorithm is compared with the original algorithm,and the optimal results are displayed by 3D visualization.The results show that the improved NSGA-Ⅱalgorithm can get more accurate Pareto resolutions set.