摘要
不确定因素经常影响部队救灾行动和效果,在资源有限、时间紧迫的情况下,克服不确定因素影响,科学进行部队驻地选址、救灾任务分配,规划好各救灾分队的搜救线路,实现救灾效果总体最优尤为重要。在假设部队行进时间和受灾点所需救灾时间均服从正态分布的基础上,建立了以救灾总费用最少和总救灾时长最小为目标的选址路径(LRP)多目标随机规划模型。引入惩罚因子,将随机约束转化成目标函数,将各目标函数值归一化求和作为适应度函数值,设计了一种改进遗传算法。通过算例实验发现,改进遗传算法和基本遗传算法惩罚值均为0,改进遗传算法总的救灾时间较短,改进蚁群算法救灾总时间短,救灾成本低,但惩罚值较大,从而验证了改进遗传算法的优越性。
Uncertain factors often affect the rescue operations and effects of troops.In the conditions of limited resources and urgent time,it is very important to select the locations of the troops,allocate the tasks of disaster relief,plan the rescue routes,organize efficient rescue,and achieve the overall optimal effect of disaster relief,overcoming the influences of uncertainty.Assuming that the time of troops′movement and the time required for disaster relief are all in normal distribution,a multi-objective stochastic programming model of location routing problem(LRP)with the minimum total cost and time of disaster relief is established.The random constraints are transformed into the objective function by introducing the penalty factors.The normalized sum of each objective function value is taken as the fitness function value.Based on this,an improved genetic algorithm is proposed.The experimental results show that the total rescue time of the improved genetic algorithm is shorter than the one of basic genetic algorithm,and the improved ant colony algorithm has shorter total relief time and lower disaster relief cost,but the penalty value is very big,which verifies the superiority of the improved genetic algorithm.
作者
黄茜
王书勤
邓少鸿
范林军
HUANG Qian;WANG Shuqin;DENG Shaohong;FAN Linjun(Department of Basic Courses,Officers College of PAP,Chengdu 610213,China;Department of Military Command,Officers College of PAP,Chengdu 610213,China;College of Economics and Management,Changsha University of Science&Technology,Changsha 410114,China;Department of Military Management,Officers College of PAP,Chengdu 610213,China)
出处
《郑州大学学报（工学版）》
CAS
北大核心
2021年第5期44-49,共6页
Journal of Zhengzhou University（Engineering Science）
基金
国家自然科学基金资助项目(61803073)
国家社会科学基金军事学项目(2019-SKJJ-C-098)
四川省教育厅课题(18zb0694)。
关键词
LRP
遗传算法
优化
随机规划
时间窗
location-routing problem
genetic algorithm
optimization
stochastic programming
time window
