Generation Gap

本文探讨了代沟这一热点话题,分析了年轻人与长辈间存在的分歧,包括生活方式的选择、期望的不同及社会变迁速度等深层次原因。

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Generation gap seems a hot topic between the old and the young. Parents complain that children don’t show them proper respect and obedience, while children complain that their parents don't understand them at all. Often they discover that they have very little in common.  
One cause of the generation gap is the opportunity that young people have to choose their own life. In traditional societies, children lived in the same area as their parents, married people their parents knew and approved of, and often continued the family occupation.   
In our society, people often move out of the home at an early age, marry or live with people their parents have never met, and choose occupations that are rather different. Parents often expect their children to be better than them. However, these ambitions for their children are another cause of the division between them.   
Finally, the speed of change in our society is another cause of it. In the traditional culture, people are valued for their wisdom, but in our society the knowledge of a lifetime may become out of date.   
No doubt, the generation gap will continue to be a feature of our life. Its causes are rooted in the freedoms and opportunities of our society, and in the rapid pace at which society changes.
``` % 遗传算法求解低碳冷链物流配送路径优化问题 clear clc close all NIND=100; %种群大小 MAXGEN=800; %迭代次数 Pc=0.9; %交叉概率 0-1 Pm=0.1; %变异概率 0-1 GGAP=0.9; %代沟(Generation gap) %% 输入数据 filename = 'T数据.xlsx'; % 读取的坐标数据 cities = xlsread(filename, 'B2:C32'); % 所有点坐标 % % 目的地坐标 data.X = xlsread(filename, 'B3:C32'); % 坐标 % % 目的地需求量 data.Demand=xlsread(filename, 'D3:D32'); data.ExpectTime=xlsread(filename, 'E3:F32'); % 户期望时间 % % 配送中心, data.Xstart = xlsread(filename, 'B2:C2'); % 车辆最大装载量 data.DemandMax=2000; % 千克 % 车速 data.v= 1; %千米/分钟 h=pdist(cities); tempD = squareform(h); % 举例矩阵 for i=1:size(tempD,1) for j=i:size(tempD,1) tempD(j,i)=tempD(i,j); %对称矩阵的特性是,对于所有的 i 和 j,tempD(i,j) 等于 tempD(j,i)。如果由于某种原因(如计算误差、数据输入错误等),tempD 加载后不是对称的,这段代码将确保它的对称性。 %由于 j 是从 i 开始遍历的,所以只会处理矩阵的上三角部分(包括对角线),并将这些值复制到对应的下三角部分。这样,既确保了对称性,又避免了不必要的重复计算。 end end data.D=tempD(2:end,2:end); % 目的地之间的距离 data.Startdistance=tempD(1,2:end); % 配送中心到目的地之间的距离 data.T=data.D/data.v; % 目的地之间的运动时间 data.StartT=data.Startdistance/data.v; % 配送中心到目的地之间的运动时间 [gb,Maxadaptfuncvalue]=GA(NIND,MAXGEN,Pc,Pm,GGAP,data); disp(num2str(gb)) %显示Gb的字符串形式(数字形式) disp('-------------------------------------------------------------------------------') %显示分隔符做分割 [Value,Matrix,result]=PathLength(gb,data); plot(Maxadaptfuncvalue,'LineWidth',1.5); xlabel('迭代次数') ylabel('目标函数值') grid on %% 绘图 X=[data.Xstart;data.X]; draw_Best(gb,X,Matrix,data.DemandMax) %% 数据输出 disp(['最低总成本为:', num2str(Value)]) CarNumb = max(Matrix(2,:)); % 车辆数 tempNumber=1:CarNumb; % 结果输出 disp('-------------------------------------------------------------------------------') for i = 1:length(tempNumber) fprintf('车辆编号:%d 固定成本:%d 运输成本:%6.3f 制冷成本:%6.3f 惩罚成本:%d\n', tempNumber(i), result.GudingCost(i), result.YunshuCost(i), result.ZhilengCost(i), result.ChengfaCost(i)) end disp('========================================================================') disp('各成本汇总') disp(['固定成本:', num2str(result.F1), ' 运输成本:', num2str(result.F2), ' 制冷成本:', num2str(result.F3), ' 惩罚成本:', num2str(result.F4), ' 总碳排放成本:', num2str(result.F5), ' 总成本:', num2str(result.F_ALL)])```这段代码中,我想添加出一段选择燃油车还是新能源车的代码,怎么修改,你能帮我修改吗
03-27
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