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文章编号: 16726987(2018)06009908; DOI: 10.16351/j.16726987.2018.06.016
张淑军1, 万倩男1,2, 刘国柱1, 王春2
(1.青岛科技大学 信息科学技术学院,山东 青岛 266061;2.中国石油化工股份有限公司青岛安全工程研究院,山东 青岛 266071)
摘要: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NSGAⅡ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NSGAⅡ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NSGAⅡ算法能够得到更加准确的Pareto解集。
关键词: 消防车调度优化; NSGAⅡ算法; 基因分组; 目标函数优先级; 三维可视化
中图分类号: TP 39文献标志码: A
引用格式: 张淑军, 万倩男, 刘国柱, 等. 基于改进NSGAⅡ算法的消防车辆调度优化\[J\]. 青岛科技大学学报(自然科学版), 2018, 39(6): 99106.
ZHANG Shujun, WAN Qiannan, LIU Guozhu, et al. Fire trucks scheduling optimization based on improved NSGAⅡ algorithm\[J\]. Journal of Qingdao University of Science and Technology(Natural Science Edition), 2018, 39(6): 99106.
Fire Trucks Scheduling Optimization Based on Improved NSGAⅡ Algorithm
ZHANG Shujun1, WAN Qiannan1,2, LIU Guozhu1, WANG Chun2
(1.College of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061,China;
2.Sinopec Research Institute of Safety Engineering, Qingdao 266071,China)
Abstract: Aiming atlimitations of conflict solution and low accuracy of traditional multiobjective optimization algorithm in fire trucks scheduling, an improved NSGAⅡ algorithm 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 NSGAⅡ algorithm is compared with the original algorithm, and the optimal results are displayed by 3D visualization. The results show that the improved NSGAⅡ algorithm can get more accurate Pareto resolutions set.
Key words: fire truck scheduling optimization; NSGAⅡ algorithm; gene grouping; priority of objective functions; 3D visualization
收稿日期: 20171206
基金项目: 山东省重点研发计划项目(2017GGX10127);山东省自然科学基金项目(ZR2014FM015).
作者简介: 张淑军(1980—),女,副教授,博士.