六类客房的预定数量MATLAB求解如下： >> manzhufang=[154,104,32,107,68,41]; womanzhufang=[78,48,17,59,28,19]; t=sum(manzhufang)+sum(womanzhufang); r1=manzhufang./t; r2=womanzhufang./t; C=668; for i=1:3 zhufang(i)=ceil(r1(i)*C/2)+ceil(r2(i)*C/2); end for i=4:6 zhufang(i)=ceil(r1(i)*C)+ceil(r2(i)*C); end zhufang %六类客房的预定数量 zhufang = 104 69 23 148 86 54 每位代表实际与会的概率MATLAB计算如下：表8
>> %每位代表实际与会的概率 >> a=[315,356,408,711]; >> f1=0.8984; >> for i=1:4 N=a(i)*f1 end N = 282.9960 N = 319.8304 N = 366.5472 N = 638.7624 >> N=[283,320,367,693]; >> d=[283,310,362,602]; >> for i=1:4 p=d(i)/N(i) end p = 1
15
p = 0.9688 p = 0.9864 p = 0.8687 >> p1=1.0000,0.9688,0.9864,0.8687 >> for i=1;4 q=p1(1)+p1(2)+p1(3)+p1(4) end ans = 4 q = 3.8239 >> q/4 ans = 0.9560 平均房价：表9
>>%平均房价计算 a=[50*180+30*220+30*180+20*220+50*140+35*160+30*180+35*200+50*150+24*180+27*150+50*140+45*200+35*140+35*160+40*200+40*160+40*170+30*180+30*220+50*150+40*160+30*300+40*180+40*160+45*180+30*260+30*260+30*280+30*280+55*260+45*280] a = 229870 >>b=[50+30+30+20+50+35+30+35+50+24+27+50+45+35+35+40+40+40+30+30+50+40+30+40+40+45+30+30+30+30+55+45] b = 1191 >> c=a/b c = 193.0059
各个宾馆之间距离的系数值：表10
16
各个宾馆之间距离的系数值： A=[0,150,900,650,600,600,300,500,650,1300;150,0,750,500,750,750,450,650,800,1450;900,750,0,250,1500,1500,1200,1000,1150,2200;650,500,250,0,1250,1250,950,1150,1300,1950;600,750,1500,1250,0,600,300,500,650,1300;600,750,1500,1250,600,0,300,500,350,700;300,450,1200,950,300,300,0,200,350,1000;500,650,1000,1150,500,500,200,0,150,1200;650,800,1150,1300,650,350,350,150,0,1050;1300,1450,1200,1950,1300,700,1000,1200,1050,0]; >> [V,D]=eig(A)%%求矩阵的最大特征值和特征向量 V = 0.2481 0.0239 0.2360 0.2437 -0.3029 -0.2242 -0.0056 0.7266 -0.0171 -0.0123 0.2673 0.1494 0.1580 0.2945 -0.3237 -0.2027 -0.3175 -0.6163 0.0104 -0.0302 0.4103 0.5681 -0.1935 -0.3790 0.0950 -0.0823 -0.1124 0.0891 0.4778 -0.4095 0.3655 0.5215 -0.1784 0.1772 0.0845 0.3349 0.2358 -0.0037 -0.3903 0.3590 0.3222 -0.2586 0.3235 0.1133 0.8068 -0.0428 -0.2962 0.0615 0.0844 -0.1032 0.2818 -0.3327 0.0924 0.1522 -0.3003 0.7779 -0.2461 0.0876 0.2976 -0.6357 0.2286 -0.2315 0.3235 -0.0004 0.0067 0.0422 0.6351 -0.1874 0.4143 0.1330 0.2590 -0.2060 0.3334 -0.5276 -0.0111 -0.3518 0.3499 -0.1589 -0.5274 -0.1412 0.2803 -0.2691 0.2349 -0.5285 -0.2113 0.0245 -0.3665 0.0896 0.0959 0.4278 0.4288 -0.1906 -0.6826 0.2919 -0.0381 -0.2380 0.1498 -0.0657 -0.2536 0.2588 D = 1.0e+003 * 7.8476 0 0 0 0 0 0 0 0 0 0 -3.2315 0 0 0 0 0 0 0 0 0 0 -2.0673 0 0 0 0 0 0 0 0 0 0 -1.0271 0 0 0 0 0 0 0 0 0 0 -0.6779 0 0
17
0 0 0 0 0 0 0 0 -0.4349 0 0 0 0 0 0 0 0 0 0 -0.1993 0 0 0 0 0 0 0 0 0 0 -0.1211 0 0 0 0 0 0 0 0 0 0 -0.0211 0 0 0 0 0 0 0 0 0 0 -0.0673 >> a=V(:,1) a = 0.2481 0.2673 0.4103 0.3655 0.3222 0.2818 0.2286 0.2590 0.2803 0.4288 >> a./sum(a) ans = 0.0802 0.0865 0.1327 0.1182 0.1042 0.0911 0.0739 0.0838 0.0906 0.1387 18
定会议室与客车数量：表11 model: sets:
num_i/1..8/:L,Q1,h,W; num_j/1..3/:t,Q2,n; endsets data:
Q1=1500,1200,1000,1500,1200,1000,800,1000; h=1,2,2,1,1,1,2,1;
W=200,200,226,226,122,122,132,132; Q2=800,700,600; n=45,36,33; m=668; enddata
[OBJ]min=@sum(num_i(i):Q1(i)*L(i))+@sum(num_j(j):t(j)*Q2(j)); @sum(num_i(i):L(i))=6;
@for(num_i(i):L(i)<=h(i););
@sum(num_j(j):t(j)*n(j))>=m-@sum(num_i(i):L(i)*W(i)/6); @for(num_i(i):L(i)>=0;@gin(L(i));); @for(num_j(j):t(j)>=0;@gin(t(j));); end
Global optimal solution found.
Objective value: 14600.00 Extended solver steps: 1 Total solver iterations: 54
Variable Value Reduced Cost M 668.0000 0.000000 L( 1) 0.000000 1500.000 L( 2) 1.000000 1200.000 L( 3) 2.000000 1000.000 L( 4) 0.000000 1500.000 L( 5) 0.000000 1200.000 L( 6) 0.000000 1000.000 L( 7) 2.000000 800.0000 L( 8) 1.000000 1000.000 Q1( 1) 1500.000 0.000000
19