露天矿生产的车辆安排数学建模论文

I的品位要求，故可舍弃。得到的车次安排如下：卡车编号运行线路运行车次1R(1,4)442R(2,2)393R(2,3)19R(10,5)14R(3,1)18R(10,3)15R(3,3)206R(3,4)357R(5,2)358R(5,2)359R(7,3)4210R(7,5)25R(7,2)111R(8,1)29R(10,3)112R(8,1)29R(10,3)1表9模型二的卡车分配13R(10,5)4514R(1,4)37R(2.4)515R(1,2)15R(2,2)10R(2,4)716R(2,4)16R(3,4)15R(3,1)117R(3,1)1R(3,3)6R(7,3)1R(7,5)3R(8,5)12R(8,1)118R(5,4)1R(5,5)12R(5,2)1R(7,2)11R(10,5)119R(8,3)25R(10,3)1020R(10,3)2R(10,5)34R(7,2)7至此，模型二的求解结束，选择1、2、3、5、7、8、10共7个铲点，出动20辆卡车，获得的最大产量为100716吨，其中矿石产量为55594吨，岩石产量为45122吨。五．模型的评价优点：1.模型中假设车次都是往返于指定线路，简化了问题，便于找到合适的线性模型，同时也符合实际，便于工作人员对车辆进行调度。2.在车次安排上面，充分考虑了线路问题，为尽可能减少空载运行距离，当线路变动时，并不是盲目变动，而是选择就近线路继续运输，这样一来有些车次完成任务后并不需要回到原来的铲点，直接从卸点开始另外的任务，节省了时间和路程。缺点：1.模型中后半部分的车辆安排，计算量太大，由于时间关系并未给出合理的计算程序或快捷的通用算法，不易于推广。2.在分配变动车次时，有些变动卡车需要从一个铲位调到另一个铲位工作，其中定要再消耗一定时间和里程，本次计算中并未考虑，在实际中会引起矛盾。3.对于模型一和模型二求出的最优解只是相对于选定的铲位而言，并不是对10个铲位而言的最优解，由于对于每种模型铲位的选取都有=120种可能，穷举运算量太大，所以只是选取了相对好的解。参考文献【1】网络优化赫孝良【2】姜启源，谢金星，叶俊.数学模型.高等教育出版社.2011.1【3】露天矿生产的车辆安排赵航陈哲李辉【4】李继承.数学实验.高等教育出版社.2006.10【5】工程数学学报2003年12月第20卷第7期文章编号：1005-3085（2003）07-0069-07【6】工程数学学报2003年12月第20卷第7期文章编号：1005-3085（2003）07-0083-07【7】四川理工学院学报（自然科学版）2004年12月第17卷第3•4期文章标号1008-438X（2004）03-04-0099-05附录一data:kuangshi=9500,10500,10000,10500,11000,12500,10500,13000,13500,12500;yanshi=12500,11000,13500,10500,11500,13500,10500,11500,13500,12500;hantieliang=0.3,0.28,0.29,0.32,0.31,0.33,0.32,0.31,0.33,0.31;shiliao=12000,13000,13000,19000,13000;juli=5.261.94.420.645.895.190.993.861.765.614.211.93.721.275.6141.133.161.834.562.951.272.252.743.512.742.252.812.63.652.461.480.784.212.461.92.041.623.722.460.643.091.275.051.061.273.510.56.10.57;enddatamin=@sum(link:154*checi*juli);@for(chandian(i):@sum(xiedian(j)|j#LT#4:154*checi(i,j))<=kuangshi(i););@for(chandian(i):@sum(xiedian(j)|j#GT#3:154*checi(i,j))<=yanshi(i););@for(xiedian(j):@sum(chandian(i):154*checi(i,j))>=shiliao(j););@for(xiedian(j)|j#LT#4:(@sum(chandian(i):154*checi(i,j)*hantieliang(i)))/(@sum(chandian(i):154*checi(i,j)))>=0.285;);@for(xiedian(j)|j#LT#4:(@sum(chandian(i):154*checi(i,j)*hantieliang(i)))/(@sum(chandian(i):154*checi(i,j)))<=0.305;);@for(chandian(i):@sum(xiedian(j):5*checi(i,j))<=480;);@for(xiedian(j):@sum(chandian(i):3*checi(i,j))<=480;);@for(link:@gin(checi););附录二data:kuangshi=9500,10500,10000,10500,11000,12500,10500,13000,13500,12500;yanshi=12500,11000,13500,10500,11500,13500,10500,11500,13500,12500;hantieliang=0.3,0.28,0.29,0.32,0.31,0.33,0.32,0.31,0.33,0.31;shiliao=12000,13000,13000,19000,13000;juli=5.261.94.420.645.895.190.993.861.765.614.211.93.721.275.6141.133.161.834.562.951.272.252.743.512.742.252.812.63.652.461.480.784.212.461.92.041.623.722.460.643.091.275.051.061.273.510.56.10.57;enddatamax=@sum(link:154*checi);@for(chandian(i):@sum(xiedian(j)|j#LT#4:154*checi(i,j))<=kuangshi(i););@for(chandian(i):@sum(xiedian(j)|j#GT#3:154*checi(i,j))<=yanshi(i););@for(xiedian(j):@sum(chandian(i):154*checi(i,j))>=shiliao(j););@for(xiedian(j)|j#LT#4:(@sum(chandian(i):154*checi(i,j)*hantieliang(i)))/(@sum(chandian(i):154*checi(i,j)))>=0.285;);@for(xiedian(j)|j#LT#4:(@sum(chandian(i):154*checi(i,j)*hantieliang(i)))/(@sum(chandian(i):154*checi(i,j)))<=0.305;);@for(chandian(i):@sum(xiedian(j):5*checi(i,j))<=480;);@for(xiedian(j):@sum(chandian(i):3*checi(i,j))<=480;);@for(link:@gin(checi););end附录三model:title:mineproblem;sets:chandian/1..7/:kuangshi,yanshi,hantieliang;xiedian/1..5/:shiliao;link(chandian,xiedian):checi,juli;endsetsdata:kuangshi=9500,10500,10000,11000,10500,13000,12500;yanshi=12500,11000,13500,11500,10500,11500,12500;hantieliang=0.3,0.28,0.29,0.31,0.32,0.31,0.31;shiliao=12000,13000,13000,19000,13000;juli=5.261.94.420.645.895.190.993.861.765.614.211.93.721.275.612.951.272.252.743.512.461.480.784.212.461.92.041.623.722.461.273.510.56.10.57;enddatamax=@sum(link:154*checi);@for(chandian(i):@sum(xiedian(j)|j#LT#4:154*checi(i,j))<=kuangshi(i););@for(chandian(i):@sum(xiedian(j)|j#GT#3:154*checi(i,j))<=yanshi(i););@for(xiedian(j):@sum(chandian(i):154*checi(i,j))>=shiliao(j););@for(xiedian(j)|j#LT#4:(@sum(chandian(i):154*checi(i,j)*hantieliang(i)))/(@sum(chandian(i):154*checi(i,j)))>=0.285;);@for(xiedian(j)|j#LT#4:(@sum(chandian(i):154*checi(i,j)*hantieliang(i)))/(@sum(chandian(i):154*checi(i,j)))<=0.305;);@for(chandian(i):@sum(xiedian(j):5*checi(i,j))<=480;);@for(xiedian(j):@sum(chandian(i):3*checi(i,j))<=480;);@for(link:@sum(link:checi*(8+30*juli/7))<=9600;);@for(link:@gin(checi););end附录四model:title:mineproblem;sets:chandian/1..7/:kuangshi,yanshi,hantieliang;xiedian/1..5/:shiliao;link(chandian,xiedian):checi,juli;endsetsdata:kuangshi=9500,10500,10000,10500,13000,13500,12500;yanshi=12500,11000,13500,10500,11500,13500,12500;hantieliang=0.3,0.28,0.29,0.32,0.31,0.33,0.31;shiliao=12000,13000,13000,19000,13000;juli=5.261.94.420.645.895.190.993.861.765.614.211.93.721.275.6141.133.161.834.561.92.041.623.722.460.643.091.275.051.061.273.510.56.10.57;enddatamax=@sum(link:154*checi);@for(chandian(i):@sum(xiedian(j)|j#LT#4:154*checi(i,j))<=kuangshi(i););@for(chandian(i):@sum(xiedian(j)|j#GT#3:154*checi(i,j))<=yanshi(i););@for(xiedian(j):@sum(chandian(i):154*checi(i,j))>=shiliao(j););@for(xiedian(j)|j#LT#4:(@sum(chandian(i):154*checi(i,j)*hantieliang(i)))/(@sum(chandian(i):154*checi(i,j)))>=0.285;);@for(xied