2011数学建模B题图形画法
2011年数学建模B题答案
2011年数学建模B题答案load B1.txt %巡警站点号、横坐标、纵坐标（前三列）load B2.txt %起始点，末端位置号（两列）hzb=B1(:,2);%横坐标zzb=B1(:,3);%纵坐标start=B2(:,1);%起始位置fina=B2(:,2);%末端位置n=length(hzb);%坐标个数m=length(start);%起始点个数：含重复a=ones(n,n);%n阶矩阵b=10000.*a;%b为矩阵a的值乘上10000for i=1:m %每个始点出去x=start(i);y=fina(i);if y<=92s=((hzb(x)-hzb(y))^2+(zzb(x)-zzb(y))^2)^0.5;b(x,y)=s;b(y,x)=s;%双向图距离endendpath=zeros(n,20);%终点前一个路劲节点distance=b(:,1:20);%二十个站到其他点的最短距离u=0;mindis=10000;%最短距离初始为10000flag=1;s=zeros(n,1);for i=1:20s=0.*s;%每次清零flag=1;%bool型标量for j=1:nif distance(j,i)<10000path(j,i)=i;%若满足，就往下走endends(i)=1;for j=1:n% if flag==1mindis=10000;for k=1:nif s(k)==0 & distance(k,i)<mindisu=k;mindis=distance(k,i);%选择最小的赋给mindisendend% if mindis>30% flag=0;% ends(u)=1;for k=1:nif s(k)==0 & b(u,k)<10000 & distance(u,i)+b(u,k)<distance(k,i)distance(k,i)=distance(u,i)+b(u,k);path(k,i)=u; %选择最短路径endend% endendendfor i=1:20for j=1:nifdistance(j,i)<10000&fprintf(' %d %d %f,%d\n',i,j,distance(j,i),pa th(j,i));%fprintf('%d %d %f %d\n',i,j,distance(j,i),path(j ,i));%fprintf('%f\n',distance(j,i)); %输出路径，始点，终点，及终点前一个结点endendend数学建模文章格式模版题目：明确题目意思一、摘要：500个字左右，包括模型的主要特点、建模方法和主要结果二、关键字：3－5个三．问题重述。
2011全国数学建模竞赛B题附件2
全市路口节点标号路口所属区域1413359A 1.7说明：2403343A 2.13383.5351A 2.24381377.5A 1.75339376A 2.16335383A 2.57317362A 2.48334.5353.5A 2.49333342A 2.1坐标的长度单位为毫米10282325A 1.611247301A 2.612219316A 2.413225270A 2.214280292A 2.515290335A 2.116337328A 2.617415335A 2.518432371A 1.919418374A 1.820444394A 1.921251277A 1.422234271A 1.423225265A 2.424212290A 1.125227300A 1.626256301A 1.227250.5306A 0.828243328A 1.329246337A 1.430314367A 2.1路口的横坐标X 路口的纵坐标Y 发案率(次数)A列：是全市交通网络中路口节点的标号（序号）B列：路口节点的横坐标X，是在交通网络中的实际横坐标值C列：路口节点的纵坐标Y，是在交通网络中的实际纵坐标值D列：路口节点所属的区E列：各路口节点的发案率是每个路口平均每天的发生报警案件数量地图距离和实际距离的比例是1:100000,即1毫米对应100米31315351A 1.632326355A 1.5案发地P点的标号：32 33327350A 1.434328342.5A 1.735336339A 1.436336334A 1.137331335A0.138371330A 1.239371333A 1.440388.5330.5A 1.741411327.5A 1.442419344A 1.443411343A 1.744394346A 1.145342342A 1.446342348A 1.247325372A 1.648315374A 1.449342372A 1.250345382A 1.151348.5380.5A0.852351377A0.653348369A 1.454370363A0.955371353A156354374A0.557363382.5A0.858357387A 1.159351382A0.960369388A0.761335395A0.662381381A 1.2 63391375A 1.4 64392366A0.8 65395361A0.7 66398362A0.8 67401359A0.8 68405360A0.9 69410355A 1.1 70408350A0.9 71415351A 1.1 72418347A0.8 73422354A0.9 74418.5356A 1.1 75405.5364.5A0.8 76405368A 1.1 77409370A0.8 78417364A0.8 79420370A0.8 80424372A0.8 81438368A 1.4 82438.5373A 1.1 83434376A0.9 84438385A1 85440392A 1.2 86447392A 1.4 87448381A 1.1 88444.5383A0.9 89441385A 1.4 90440.5381.5A0.9 91445380A0.9 92444360A0.893140130B 1.6 94145118B 1.6 9516096B 1.6 96142.571B 2.1 9715070B 1.8 98186145B 1.6 9915873.5B 2.6 10012168B 2.6 101157145B 1.1 102158138.5B0.9 103159135B0.5 104133114B0.7 105137.5113B0.4 106144112B0.8 107139117B0.2 108144.5115B0.8 109151113B0.6 110151.5118B0.9 111150111B0.8 112158118B 1.1 113159109B0.8 114164108.5B0.4 115163105B0.7 11614999.5B 1.2 117143102B0.8 118137103B0.9 119131103B0.5 120130100B0.6 121127102B0.6 12212598B0.8 12312996B0.912413090B0.4 12512490B0.7 12613696B 1.1 12713690B0.8 12814296B0.8 12914896B0.7 13014291B0.6 13114791B0.7 13212871B 1.2 133136.576B0.8 13414279B 1.1 13514781B0.8 13615486B0.9 137148.574.5B 1.1 13814070B0.6 13914063B0.7 140137.563B0.8 14113859B0.4 14214363B 1.1 14315169B0.8 14415363B 1.1 14514360B0.7 14614357B0.6 14714351.5B0.8 14816065B 1.1 14916259B0.6 15014149B0.4 15114340B0.8 15215144B0.5 15315033B0.1 154164124B0.6155171125B0.7 156165.5139B 1.1 157181131B 1.4 158176141B 1.6 159170140B0.8 160168145B0.6 161166150B0.8 162176145B0.6 163180149B0.7 164183145B 1.1 165202131B 1.1 166137.5462C 2.6 167167399C 2.2 168376400C 1.4 169210390C 2.6 170263445C 2.2 171284409C 1.9 172278.5425C 2.2 173295382C2 174299444C 2.6 175362443C 2.2 176410408.5C 2.1 177395520C 2.2 178277496C 1.7 179235465C 2.2 180200466.5C 1.9 181167462C 2.4 182225443C 2.4 183400447C 1.2 184414422C 1.4 185424400C 1.2186411396C 1.4 187420401C0.8 188403404C 1.2 189376406C0.9 190380404C0.8 191377424C0.8 192374424C0.8 193370423C0.4 194368427.5C0.9 195374431C 1.2 196365448C 1.4 197356450C 1.4 198358459C 1.2 199354495C 1.1 200357513C 1.2 201359528C0.4 202347553C0.5 203261537.5C0.8 204270514C 1.4 205313511.5C0.4 206324511C0.8 207333511C0.7 208334497C0.8 209323497C0.7 210312498C 1.1 211317451C 1.1 212316448C0.8 213315.5444C0.7 214316434C0.9 215318412C 1.2 216291.5415C 1.4217284425C 1.4 218281421C 1.6 219299434C 1.4 220302451C 1.4 221305457C 1.2 222281458.5C 1.1 223274448C0.8 224273.5444C0.9 225267446C 1.1 226270440C0.9 227275422C 1.1 228276419C 1.2 229270415C0.8 230276405C 1.4 231288403C 1.4 232293.5392.5C 1.4 233296387C 1.1 234303386C 1.4 235298.5378C 1.6 236293376C 1.2 237296372C 1.7 238276352C1 239250350C 1.4 240247384C 1.2 241262399C 1.4 242269397C 1.2 243276402C 1.3 244282398.5C 1.2 245282386.5C 1.1 246273389C 1.2 247276361C 1.1248138.5378C0.8 249155396C 1.2 250163390C 1.5 251173364C 1.2 252183370C 1.2 253238382C0.7 254213412C0.8 255189413C 1.1 256210433C0.9 257201434C0.9 258150400C 1.2 259135395C 1.2 260143407C 1.1 261142414C0.8 262140430C 1.1 263121432C0.9 264109441C0.5 265138.5442C 1.2 266167442C 1.6 267168435C 1.4 268184440C 1.2 269194442C0.9 270200442C 1.4 271212443C 1.6 272220443C 1.7 273246444C 2.1 274246455C 1.4 275252458C 1.2 276257460.5C 1.5 277255.5466C 1.2 278249464C 1.1279247469C0.8 280254472C0.7 281251.5477C 1.1 282259478C0.8 283261470C0.4 284255494C 1.4 285240495C 1.4 286241514C0.8 287236514C0.7 288235496C0.7 289232487C0.8 290235.5486.5C0.8 291245474C 1.2 292225457.5C 1.4 293225451C 1.6 294219451C 1.4 295219462C 1.2 296228.5472C 1.6 297213481C 1.4 298211487C1 299208.5496C 1.2 300206507C0.8 301206515C 1.2 302200514C0.7 303200507C 1.2 304200497C 1.3 305200484C 1.4 306206466C 1.4 307194466C 1.4 308184463.5C 1.5 309184475C0.8310193.5475C0.7 311193484C0.9 312184484C0.6 313184496.5C0.8 314192.5496.5C0.7 315192507C0.9 316192514C0.8 317170516.5C0.6 318168507C 1.1 319167495.5C 1.4 320101343D 2.4 32191355D 1.7 32270377D 2.5 32346371D 2.4 32456424D 2.1 32520442D 2.2 32674326D 2.6 32776302D 2.1 32815240D 2.6 32928161D0.4 33034.5164.5D0.1 33130181D0.6 33227206D0.2 33342242D 1.4 33430246D 1.6 33531254D 1.1 33639254D 1.2 33750289D0.7 33872288D 1.1 33960246D0.7 34095299D 1.434181297D 1.6 34280287D 1.4 34367314D 1.7 34421330D 1.1 34536360D 1.2 34676344D0.8 34797339D 2.4 348103337D 1.2 349104341D 1.1 35097345D 1.6 35189345D0.8 35281344.5D0.8 35381350D0.4 35489350D0.7 35592.5351.5D 1.1 35688353D 1.4 35781.5353D0.9 35887359D 1.1 35984361D0.9 36076355D0.8 36158.5370D0.6 36234306D0.1 36338418.5D 1.4 36461425D 1.4 36557429D 1.6 36660433D 1.4 36785369D 1.9 368107.5362D 1.4 369131366.5D 1.2 370170342D 1.2 371174340D 1.5372232.5264E 2.4 373202223E 1.9 374241210E 2.4 375235197.5E 2.6 376228173E 2.6 377214164E 2.6 378278196E 2.6 379267168E 2.4 38090167E1 381123177.5E 1.1 382143153E 1.9 383192264E 2.6 384145285E 2.4 385133255E 2.4 38690198E 1.7 3872115E 1.1 3886068E0.8 3897084E0.2 39027149E 1.6 39162143E0.9 39258176E 1.4 39358160E0.6 39472163E0.7 39570176.5E0.7 39690178E0.8 397115168E0.6 398115177.5E0.8 399123168E0.7 400123164E0.6 401123155E0.7 402143164E0.9403144168E 1.2 404149177E0.9 405128178E0.9 406128188E 1.5 407164194E 1.7 408156177E0.8 409168177E 1.1 410156169E0.8 411167168E0.8 412172167E0.9 413167164E0.2 414160164E0.7 415163153.5E 1.2 416186168E 1.6 417269133E 1.6 418295112E 1.1 419302112E 1.4 420316141E 1.6 421278143E 1.7 422284173E 1.4 423257.5170E 1.9 424239198E0.4 425241198E0.3 426246199E0.6 427246.5202E0.4 428240202E0.4 429236201E 1.1 430231199E0.1 431232206.5E0.6 432239.5207.5E0.5 433242206E0.2434235209.5E0.4 435237.5212E0.1 436246208E0.4 437200194E 1.1 438170222E 1.6 43959189E0.8 44072189E0.9 44190187.5E0.6 44274198E0.7 44360196E0.4 44490211E 1.6 445151236E 1.4 446160244E 1.5 44790222E0.8 448129248E 1.7 449142265E 2.1 450152255.5E 1.1 451155258E0.6 452163258E0.8 453171258E 1.1 454171252.5E0.4 455171247E 1.2 456214235E 1.1 457244238E 1.1 458268237E 1.1 459259255E 1.1 460188261E 1.4 461184253E 1.2 462171263E 1.1 463171268E0.8 464163268E0.9465154268.5E0.7 466151275E0.4 467148274E 1.5 468162277.5E 1.5 469177281E0.7 470187284E 1.4 471155316E 1.6 472159292E 1.8 473125267E 1.8 474107285E 1.6 475382.5267F 2.4 476373250F 1.9 477330219F0.8 478400247F 2.3 479441442F 1.7 480417312F 1.5 481332246F 1.9 482321275F 1.7 483403140F 2.1 484420269F 2.4 485455335F 1.9 486295.5238F 1.4 487294244F 1.1 488316300F 1.5 489308257.5F 1.2 490327255F0.8 491316236F 1.4 492314230F0.9 493313223F0.6 494317215F0.2 495318.5222F0.3496320229F0.5 497326.5227.5F0.7 498325220F0.6 499323213F0.4 500329212F0.7 501332226F0.7 502334210.5F0.6 503346209F0.7 504342200F0.8 505356202F0.7 506358195F0.6 507345194F0.4 508348188F0.4 509357.5188F0.6 510359159F 1.1 511404161F 1.2 512403202F0.8 513379202F0.7 514386213F0.8 515373213F0.6 516363212F0.4 517362218F0.8 518354216.5F0.6 519348215F0.9 520349222F0.7 521353223F0.8 522371224F0.8 523371218.5F0.6 524375219F0.4 525388.5218F 1.1 526405213.5F0.8527389224.5F0.9 528388233F0.6 529353229.5F0.8 530334232F0.7 531336239F 1.1 532352247F 1.2 533353236F0.6 534362.5236F0.8 535370236F 1.1 536388237F 1.2 537395.5237.5F 1.4 538395233F 1.1 539408.5227F 1.5 540430237F 1.4 541450268F0.1 542394254F 1.4 543387250F0.9 544383250F 1.1 545369249.5F0.8 546367.5249F0.7 547362249F0.8 548350251F0.6 549348255F 1.4 550355265F 1.1 551367265F0.8 552367257.5F 1.2 553375258F 1.4 554376260F 1.1 555381260F 1.7 556378266F 1.4 557380270.5F 1.2558371284F 1.1 559356.5281F 1.4 560338297F 1.2 561372307F 1.4 562398308F 1.5 563392277F 1.1 564382.5276F0.9 565396270F 1.4 566411291F 1.2 567424297F0.8 568435319F0.9 569434307F0.7 570430295F 1.4 571441309F 1.2 572470342F0.2 573468432F 1.2 574455361F0.6 575453400F0.6 576425433F0.8 577462437F 1.4 578481457F0.6 579462447F 1.2 580440449F 1.4 581423448F1 582435507.5F0.4路线终点（节点）标号说明：17517824434536543946354955065973274789847935103411221126122512471142115715311614163817401742178118811883路线起点(节点）标号A列：全市交通网中连接两路口节点路线的起点标号B列：全市交通网中连接两路口节点路线的终点标号1979 2086 2122 22372 2213 2313 23383 2413 2425 2511 2627 2610 2712 2829 2815 2930 307 3048 3132 3134 3233 3334 338 349 3545 3635 3637 3616 3639 377 38393841 3940 402 4117 4192 4243 432 4372 443 4546 468 4655 4748 476 475 4861 4950 4953 5051 5152 5159 5256 5352 5354 5455 5463 553 5657 5758 5760 5745859 6062 6160 624 6285 6364 6465 6476 6566 6667 6676 6744 6768 6869 6875 6970 6971 691 702 7043 7172 7174 7273 7374 7318 741 7480 7576 7677 7778 77197879 7980 8018 8182 8283 8290 8384 8485 8520 8687 8688 8788 8792 8889 8891 8920 8984 8990 9091 9192 93104 94110 95116 95136 96137 96138 96142 9799 97143 98165 99148100132 100150 101102 102103 102156 10393 103154 104105 105106 105107 106111 106117 10794 10894 108107 108106 108109 109110 110112 111109 111113 112113 113114 113116 114115 114154 11595 115165 116117 116129 117118117128 118105 118119 118126 119120 120121 120123 121104 121122 122123 122125 123124 123126 124125 124127 125132 126127 126128 127130 127133 128129 128130 129131 130131 130134 131135 132133 133134 133140 134135 13496135136 135137 13699 13797 138139 139140 139142 140141 141146 142143 142145 143144 144145 144148 145146 146147 147149 147150 148149 149152 150151 150152 151152 152153 154155 155156 155157 156159 157158 157164 158159158162 158164 159160 160161 160162 161163 162163 163164 16498 165377 166265 166181 167250 167255 168189 170225 170227 171228 171216 171231 172219 173233 173232 173236 174213 174220 175197 175196 176184 176187 177582178210 178284 179291 179274 180305 180270 180306 180307 181308 182273 183184 183196 184185 185186 186168 187185 187186 188176 188186 189190 189192 19062 190191 191192 192193 194193 194175 195194 195188 195196 196197196198 198177 198199 199200 200201 201177 201202 203202 203204 204205 204178 205206 205210 206207 207200 207208 208199 209206 209208 210209 210211 211212 212213 213214 215214 215175 216215 216217 218217 218172 219214219174 220212 221211 221220 221222 222220 222178 222223 223224 224174 225223 225226 226224 226172 227172 227228 228218 229228 229230 230171 231232 232233 233234 234168 235234 23548 235173 236237 23730 237235 237238238239 23929 239240 240241 241242 242243 243230 243244 244231 245244 245232 245236 246241 246242 246245 246247 247237 247238 248369 248239 248249 249167 250251 250252 251252 252253 253240 253254 254169 255256 256257258249 258260 259258 259248 259260 261260 261262 262263 262267 263261 263264 265262 266181 266265 266267 267255 267268 268269 269270 270257 270271 271256 271272 271295 272182 273170 273241 274273 274275 275276 276170276277 277278 277283 278275 279278 279280 280277 280281 281282 282283 284282 285284 285281 286285 286204 286203 286287 287288 288285 289288 289290 290285 290291 291281 291279 292179 292293 293182 293274 294292 294293294272 295292 295296 296179 296290 297296 298289 298297 299298 299288 300299 300301 301287 302301 302303 303300 303304 304299 305304 306297 307269 308307 308268 308309 309310 309312 310307 310311 311305 312311 312313313314 314311 314304 315303 315314 315316 316302 317264 317203 317316 317318 318315 318319 319181 319313 320350 321356 321358 321368 322367 323363 324364 324365 326347 327343 329330 329331 331392 332330 333331 333334333339 334328 334335 335336 336333 336337 337338 337343 338339 338342 338327 339447 340341 341342 341327 343344 343326 344345 345346 345323 346326 346352 346360 347348 347320 348340 348349 349320 349371 350351 350355351352 351354 352353 353354 353357 354355 354356 355321 356357 356358 357358 357360 358359 359360 359367 360361 361362 361323 361322 361264 362332 363325 363324 364367 365364 365366 366369 367368 368349 368369 369370370371 37029 37128 37223 373431 373438 373456 374436 375424 375429 375430 376375 377416 377417 377376 378458 379423 380397 381399 381405 382402 382101 38293 383460 384467 384473 385449 385473 386442 386444 387388387390 388389 388391 388100 389330 389153 390391 390329 392393 392395 392439 393391 393394 394395 394380 395396 395440 396380 396398 396441 397398 398381 399400 399403 400401 400402 401382 402403 402414 403404 403410404405 404407 404408 405406 406407 407437 407438 408409 408410 409411 410411 411412 412413 412416 413414 414415 415101 415161 415416 416437 417418 417421 418419 419420 420421 420422 421379 422379 423376 423424 423378424425 424429 425426 425428 426427 427378 427428 427436 428429 428433 429431 429432 431434 432433 432434 432374 434435 435374 437373 438446 439440 439443 440441 440442 441386 442443 444445 444332 445446 446455 447444447448 448445 448385 449450 449467 450446 450451 451452 451465 452453 453454 453462 454455 454461 455456 456457 456372 457374 457458 457372 458459 458486 45914 45921 460461 460462 462463 463464 464452 465466 466467466468 468464 468469 469463 469470 470383 47024 471472 472468 472384 474447 474473 474471 474340 475555 475565 476545 477501 478542 478566 479577 479580 480568 482489 482559 484539 484570 485571 485572 485573 486487486491 487488 488482 488560 489487 489490 490481 490550 491481 491492 491530 492493 492496 493494 493495 494495 494499 495498 496495 496497 497498 497501 498499 498477 499500 500477 500502 501520 501530 502503 502504504505 505506 505513 506507 506509 507504 508507 508509 508510 509510 510511 511512 511483 512513 513514 514515 515516 516517 517518 517523 518505 518519 518521 519503 519520 520521 521522 521529 522523 522527 523524524515 524525 525514 525526 526512 527525 528527 528529 528536 528538 529530 530531 531481 531532 532533 532547 532548 533529 533534 534535 535536 536537 537538 537478 538539 539526 539540 539478 540541 540484 542543542565 543536 543544 544476 544555 545535 545546 546547 546552 547534 548549 548552 549481 549550 550551 550559 551552 551556 552553 553476 553554 554555 556554 556475 557475 557558 557564 558559 560549 56016 56056156138 561558 561562 562563 562480 563564 563565 565566 566567 567480 567569 568569 568574 569570 569571 570571 572541 572578 573578 574575 575576 576479 577573 577579 580579 580581 581576 581582 581183 582578交巡警平台编号交巡警平台位置标号说明：A11 A22 A33 A44 A55 A66 A77 A88 A99 A1010 A1111 A1212 A1313 A1414 A1515 A1616 A1717 A1818 A1919 A2020 B193 B294 B395 B496 B597 B698 B799 B8100 C1166 C2167 C3168 C4169 C5170 C6171 C7172 C8173 C9174 C10175 C11176 C12177 C13178 C14179 C15180 C16181 C17182 D1320 D2321 D3322A列：表示全市交巡警服务平台的名称编号B列：表示全市交巡警服务平台的位置标号。
2011年B题数学建模大赛论文
交巡警服务平台的设置与调度摘要“交巡警服务平台的设置与调度”数学建模的目的是设计一个模型，建立一种利用率最高的交巡警服务平台，但是不同于普通服务平台设置与调度问题，该题需要考虑多种情况，例如，管辖区域重叠的划分，最短时间内封锁，逃跑犯人逃跑路线是离散型等等。
我们基于最短路径模型，对于题目实际情况进行研究和分析，对五个问题都设计了合适的数学模型做出了相应的解答和处理。
问题一：（1）此问需要考虑两个路口之间的位置关系，根据位置的不同设计相应的模型，我们基于道路阻抗算法，matlab的floyd算法，在不考虑道路差异的情况下，只考虑如何设计最优分配的原则，带入excel里的数据算出结果。
(2)此问基于（1）算出的数据，我们采用了0-1规划模型，运用lingo解决最优路径问题，运引入计算几何的相关理论，基于模糊数学的评价指标，设计出可行性最高的调度方案。
(3)此问题基于（1）（2）算出的数据采取运筹学知识和lingo软件，分析影响辖区内各种案件发生率的因子，确定出合理的平台设置个数方案。
问题二：（1）此问题给出了该市的相关数据（该区面积、人口、路口数、路口发案率），设置方案的合理性主要考虑各区在其主要影响因素下得出的综合因子K是否平衡，才能判断是否合理及其解决方案。
（2）在设计最佳围堵方案的时候，以 P点为根节点向各个分支逃跑线路所经过的交通路口为叶子节点，当遇到交巡警服务平台的节点后该叶子以下结束；距离p点3公里以外的节点可以作为交巡警调度围捕节点；下一级叶子节点所表示的交叉路口到该级叶子节点所表示的路口的距离加3千米小于该节点以上到达p点的距离之和，即可将下一结点的交巡警平台调往该节点进行围堵，遵循此原则，得出树形围堵方案。
对于第一问，根据给出的A区交通网络地图，运用基于matlab的floyd算法，求出最短路径，确定每个各交巡警服务平台可控分配管辖范围。
运用邻接矩阵的算法，求出92矩阵的结果，分析筛选出最短合适距离。
2011数学建模B题编程最优路径
model: sets:plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77,A78,A79,A80,A81/:L;roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78A69,A68 A69,A70 A69,A71A74,A80 A74,A71 A74,A73A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.16.79.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76 ,A78/:L;roads(plot,plot)/A2,A44 A2,A43 A2,A70A44,A67 A44,A3A43,A72 A43,A70 A43,A42A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.115.28.1 58.56.47.1 54.55.84.06.18.59.3 6.4 6.33.513.2;L=0,,,,,,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A2,A40 A2,A43 A2,A70A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:D=15.2 11.63.2 5.89.5 14.84.219.1 8 8.64.117.77.65.47.1 4.545.6 3;L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA @for(plot(i)|i#GT#@index(A3): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endmodel: sets:plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77,A78,A79,A80,A81/:L;roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78A69,A68 A69,A70 A69,A71A74,A80 A74,A71 A74,A73A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.19.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76 ,A78/:L;roads(plot,plot)/A2,A44 A2,A43 A2,A70A44,A67 A44,A3A43,A72 A43,A70 A43,A42A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.115.28.1 58.56.47.1 54.55.84.06.18.59.3 6.4 6.313.2;L=0,,,,,,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3 model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A2,A40 A2,A43 A2,A70A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:D=15.2 11.63.2 5.89.5 14.84.219.1 8 8.64.117.77.65.47.1 4.545.6 3;L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A3): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77,A78,A79,A80,A81/:L;roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78A69,A68 A69,A70 A69,A71A74,A80 A74,A71 A74,A73A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.16.79.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endmodel: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76 ,A78/:L;roads(plot,plot)/A2,A44 A2,A43 A2,A70A44,A67 A44,A3A43,A72 A43,A70 A43,A42A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.115.28.1 58.56.47.1 519.1 8 8.64.117.77.65.47.1 4.545.6 3;4.55.84.06.18.59.3 6.4 6.33.513.2;L=0,,,,,,,,,,,,,,,,,,,,; J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A2,A40 A2,A43 A2,A70A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:D=15.2 11.63.2 5.89.5 14.84.2L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A3): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets: plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77,A78,A79,A80,A81/:L;roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78A69,A68 A69,A70 A69,A71A74,A80 A74,A71 A74,A73A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.16.79.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76 ,A78/:L;roads(plot,plot)/A2,A44 A2,A43 A2,A70A44,A67 A44,A3A43,A72 A43,A70 A43,A42A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.115.28.1 58.56.47.1 54.55.84.06.18.59.3 6.4 6.33.513.2;L=0,,,,,,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A2,A40 A2,A43 A2,A70A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:D=15.2 11.63.2 5.89.5 14.84.219.1 8 8.64.117.77.65.47.1 4.545.6 3;L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A3): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets: plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77,A78,A79,A80,A81/:L;roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78A69,A68 A69,A70 A69,A71A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.16.79.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76 ,A78/:L;roads(plot,plot)/A2,A44 A2,A43 A2,A70A44,A67 A44,A3A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.115.28.1 58.56.47.1 54.55.84.06.18.59.3 6.4 6.33.513.2;L=0,,,,,,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A2,A40 A2,A43 A2,A70A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:D=15.2 11.63.2 5.89.5 14.84.219.1 8 8.64.117.77.65.47.1 4.545.6 3;L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A3): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77,A78,A79,A80,A81/:L;roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78A69,A68 A69,A70 A69,A71A74,A80 A74,A71 A74,A73A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.16.79.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endmodel: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76 ,A78/:L;roads(plot,plot)/A2,A44 A2,A43 A2,A70A44,A67 A44,A3A43,A72 A43,A70 A43,A42A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74 A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.115.28.1 58.56.47.1 54.55.84.06.18.5L=0,,,,,,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A2,A40 A2,A43 A2,A70A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:D=15.2 11.63.2 5.89.5 14.84.219.1 8 8.64.117.77.65.47.1 4.545.6 3;L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A3): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77 ,A78,A79,A80,A81/:L; roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78 A69,A68 A69,A70 A69,A71 A74,A80 A74,A71 A74,A73A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.16.79.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76,A78/:L;roads(plot,plot)/A2,A44 A2,A43 A2,A70A44,A67 A44,A3A43,A72 A43,A70 A43,A42 A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1 A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.1D=15.2 11.63.2 5.89.5 14.84.219.1 8 8.64.117.7 8.1 58.56.47.1 54.55.84.06.18.59.3 6.4 6.33.513.2;L=0,,,,,,,,,,,,,,,,,,,,; J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A2,A40 A2,A43 A2,A70A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:5.47.1 4.545.6 3;L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A3): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets: plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77,A78,A79,A80,A81/:L;roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78A69,A68 A69,A70 A69,A71A74,A80 A74,A71 A74,A73A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.16.79.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76 ,A78/:L;roads(plot,plot)/A2,A44 A2,A43 A2,A70A44,A67 A44,A3A43,A72 A43,A70 A43,A42A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.115.28.1 58.56.47.1 54.55.84.06.18.59.3 6.4 6.33.513.2;L=0,,,,,,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A2,A40 A2,A43 A2,A70A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:D=15.2 11.63.2 5.89.5 14.84.219.1 8 8.64.117.77.65.47.1 4.545.6 3;L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A3): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets: plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77,A78,A79,A80,A81/:L;roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78A69,A68 A69,A70 A69,A71A74,A80 A74,A71 A74,A73A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.16.79.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76 ,A78/:L;roads(plot,plot)/A44,A67 A44,A3A43,A72 A43,A70 A43,A42A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.115.28.1 58.56.47.1 54.55.84.06.18.59.3 6.4 6.33.513.2;L=0,,,,,,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3 model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:D=15.2 11.63.2 5.89.5 14.84.219.1 8 8.64.117.77.65.47.1 4.545.6 3;L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A3): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); end model: sets:plot/A1,A2,A3,A18,A17,A19,A42,A43,A44,A63,A64,A65,A66,A67,A68,A69,A70,A71,A72,A73 ,A74,A75,A76,A77,A78,A79,A80,A81/:L;roads(plot,plot)/A1,A69 A1,A74 A1,A75 A1,A78A69,A68 A69,A70 A69,A71A74,A80 A74,A71 A74,A73A75,A76 A75,A68A78,A79 A78,A77A68,A67A70,A2 A70,A43A71,A72A80,A79 A80,A18A73,A72 A73,A18A76,A64 A76,A66 A76,A77A79,A19A67,A44 A67,A66A2,A43 A2,A44A43,A72 A43,A42A18,A81A64,A63 A64,A65A66,A65A77,A19A42,A17A44,A3/:D;ENDSETSDATA:D=5.0 6.3 9.3 6.47.1 5.4 6.416.9 6.1 4.03.54.56.7 10.04.18.6 7.65.04.5 8.18.1 19.713.2 9.2 4.54.514.8 4.28.0 9.58.1 8.16.79.1 5.83.29.89.89.5;L=0,,,,,,,,,,,,,,,,,,,,,,,,,,,;ENDDATA@for(plot(i)|i#GT#@index(A1): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endmodel: sets:plot/A2,A1,A3,A17,A41,A42,A43,A44,A64,A65,A67,A68,A69,A70,A71,A72,A73,A74,A75,A76 ,A78/:L;roads(plot,plot)/A2,A44 A2,A43 A2,A70A44,A67 A44,A3A43,A72 A43,A70 A43,A42A70,A69A67,A68A3,A65A72,A73 A72,A71A42,A17A69,A71 A69,A68 A69,A1A68,A75A65,A64A73,A74A71,A74A17,A41A1,A75 A1,A78 A1,A74 A75,A76A64,A76/:D;ENDSETSDATA:D=9.5 8 8.614.8 11.68.1 7.6 8.15.44.115.28.1 58.56.47.1 54.55.84.06.17.65.47.1 4.545.6 3;L=0,,,,,,,,,,,,,,,;J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA 8.59.3 6.4 6.33.513.2;L=0,,,,,,,,,,,,,,,,,,,,; J v 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 JENDDATA@for(plot(i)|i#GT#@index(A2): L(i)=@MIN(roads(j,i):L(j)+D(j,i));); endA3model: sets: plot/A3,A2,A4,A38,A39,A40,A43,A44,A64,A65,A66,A67,A68,A69,A70,A75/:L; roads(plot,plot)/A3,A65 A3,A44A65,A66 A65,A64A44,A2 A44,A67A66,A67A2,A40 A2,A43 A2,A70A67,A68A40,A39A43,A70A70,A69A68,A69 A68,A75A39,A4 A39,A38/:D;ENDSETSDATA:D=15.2 11.63.2 5.89.5 14.84.219.1 8 8.64.117.7。
2011年数学建模B题答案
load B1.txt %巡警站点号、横坐标、纵坐标（前三列）load B2.txt %起始点，末端位置号（两列）hzb=B1(:,2);%横坐标zzb=B1(:,3);%纵坐标start=B2(:,1);%起始位置fina=B2(:,2);%末端位置n=length(hzb);%坐标个数m=length(start);%起始点个数：含重复a=ones(n,n);%n阶矩阵b=10000.*a;%b为矩阵a的值乘上10000for i=1:m %每个始点出去x=start(i);y=fina(i);if y<=92s=((hzb(x)-hzb(y))^2+(zzb(x)-zzb(y))^2)^0.5;b(x,y)=s;b(y,x)=s;%双向图距离endendpath=zeros(n,20);%终点前一个路劲节点distance=b(:,1:20);%二十个站到其他点的最短距离u=0;mindis=10000;%最短距离初始为10000flag=1;s=zeros(n,1);for i=1:20s=0.*s;%每次清零flag=1;%bool型标量for j=1:nif distance(j,i)<10000path(j,i)=i;%若满足，就往下走endends(i)=1;for j=1:n% if flag==1mindis=10000;for k=1:nif s(k)==0 & distance(k,i)<mindisu=k;mindis=distance(k,i);%选择最小的赋给mindisendend% if mindis>30% flag=0;% ends(u)=1;for k=1:nif s(k)==0 & b(u,k)<10000 & distance(u,i)+b(u,k)<distance(k,i)distance(k,i)=distance(u,i)+b(u,k);path(k,i)=u; %选择最短路径endend% endendendfor i=1:20for j=1:nifdistance(j,i)<10000&fprintf(' %d %d %f,%d\n',i,j,distance(j,i),path(j,i));% fprintf('%d %d %f %d\n',i,j,distance(j,i),path(j,i));%fprintf('%f\n',distance(j,i)); %输出路径，始点，终点，及终点前一个结点endendend数学建模文章格式模版题目：明确题目意思一、摘要：500个字左右，包括模型的主要特点、建模方法和主要结果二、关键字：3－5个三．问题重述。
2011全国大学生数学建模B
sij 1 sij 0 s.t. sij 1 jJ s 1 ij iI
(cij 3km) (cij 3km) (i 1 92) ( j 1 20)
s
ij
路口由一个服务台管辖： sij 1(i I )
jJ
sij 1( j J ) 服务台管辖路口数至少为1： iI
问题一（ 2 ）的思路分析与模型建立
问题一（ 2 ） 问题的数学表达：
min f 2 max cij x ij
1i 20 1 j 13
1 ，服务台i对要道j进行封锁 xij 0 ，服务台i不对要道j进行封锁
最大时间最小：
20 xij 1, j 1 13 i 1 13 s.t. xij 1, i 1 20 j 1 x 0或1 ij
问题二（ 2 ）的思路分析与模型建立
问题二（ 2 ） 问题的数学表达：
：嫌犯在t+3内行驶的最大区域
M in T s.t. flag Qt 3 , P 1
：嫌犯在t+3内行使最大区域边界点集；
1 可以分配警力，在t时间到达Qt 3中得路口 flag Qt 3 , P 0 无法分配警力，在t时间到达Qt 3中得路口
问题二
问题二：
针对全市（主城六区 A ， B ， C ， D ， E ， F ）的具体情况，按照设置 交巡警服务平台的原则和任务，分析研究该市现有交巡警服务平台 设置方案（参见附件）的合理性，如果有明显不合理，请给出解决 方案；
如果该市地点 P （第 32 个节点）处发生了重大刑事案件，在案发 3 分钟后接到报警，犯罪嫌疑人已驾车逃跑。为了快速搜捕嫌疑犯， 请给出调度全市交巡警服务平台警力资源的最佳围堵方案。
2011年数模国赛b题
2011年数模国赛b题2011年数学建模国际竞赛（简称数模国赛）是一个重要的数学竞赛活动，其中B题是其中的一道题目。
以下是对2011年数模国赛B题的多角度全面回答。
2011年数模国赛B题是什么？B题的具体内容是什么？B题涉及哪些方面的知识和技巧？B题需要用到哪些数学模型或方法？B题的解题思路和步骤是什么？B题的难度如何？B题的解答是否有唯一性？B题的解答对实际问题有何意义？B题的解答是否有局限性？B题的解答是否可以推广到其他类似问题？B题的解答是否可以优化或改进？2011年数模国赛B题是一道关于仓库布局优化的问题。
题目要求在给定的仓库平面图中，确定最佳的货架布局，以最大化仓库的存储容量。
具体而言，要求确定货架的位置和朝向，使得仓库中可以容纳最多的货物。
这道题涉及到图论、优化问题和空间布局等方面的知识和技巧。
解决这个问题需要考虑货架的位置、朝向、尺寸以及货物的尺寸和堆叠方式等因素。
同时，还需要考虑仓库的布局限制和安全要求等因素。
在解决这个问题时，可以运用数学建模的方法，建立数学模型来描述仓库布局和货物堆叠的情况。
可以使用图论来表示仓库平面图和货架的连接关系，使用优化算法来寻找最佳的货架布局，并使用数值计算方法来评估不同布局方案的存储容量。
解题的思路和步骤可以分为以下几个部分，首先，对仓库的平面图进行分析，确定仓库的尺寸和布局限制；然后，根据货物的尺寸和堆叠方式，确定货架的尺寸和摆放规则；接下来，建立数学模型，将仓库布局问题转化为优化问题；然后，使用适当的优化算法，求解最佳的货架布局方案；最后，对所得结果进行评估和优化。
这道题的难度较高，需要综合运用图论、优化算法和数值计算等知识和技巧。
解答过程中需要考虑多个因素的综合影响，同时还要注意问题的实际背景和限制条件。
这道题的解答并不唯一，可能存在多个最佳的货架布局方案。
具体的解答取决于问题的具体设置和所使用的优化算法。
这道题的解答对实际问题具有重要意义。
2011高教社杯全国大学生数学建模竞赛B题(题目改变)参考答案
交巡警服务平台的设置与调度优化分析摘要本文综合应用了Floyd算法，匈牙利算法，用matlab计算出封锁全市的时间为1.2012小时。
并在下面给出了封锁计划。
为了得出封锁计划，首先根据附件2的数据将全市的道路图转为邻接矩阵，然后根据邻接矩阵采用Floyd算法计算出该城市任意两点间的最短距离。
然后从上述矩阵中找到各个交巡警平台到城市各个出口的最短距离，这个最短距离矩阵即可作为效益矩阵，然后运用匈牙利算法，得出分派矩阵。
根据分派矩阵即可制定出封锁计划：96-151,99-153,177-177,175-202,178-203,323-264,181-317, 325-325,328-328，386-332,322-362,100-387,379-418,483-483, 484-541,485-572。
除此以外，本人建议在编号为175的路口应该设置一个交巡警平台，这样可以大大减少封锁全市的时间，大约可减少50%。
关键词: Floyd算法匈牙利算法 matlab一、问题重述“有困难找警察”，是家喻户晓的一句流行语。
警察肩负着刑事执法、治安管理、交通管理、服务群众四大职能。
为了更有效地贯彻实施这些职能，需要在市区的一些交通要道和重要部位设置交巡警服务平台。
每个交巡警服务平台的职能和警力配备基本相同。
由于警务资源是有限的，如何根据城市的实际情况与需求合理地设置交巡警服务平台、分配各平台的管辖范围、调度警务资源是警务部门面临的一个实际课题。
试就某市设置交巡警服务平台的相关情况，建立数学模型分析研究下面的问题：警车的时速为60km/h, 现有突发事件，需要全市紧急封锁出入口，试求出全市所有的交巡警平台最快的封锁计划，一个出口仅需一个平台的警力即可封锁。
二、模型假设1、假设警察出警时的速度相同且不变均为60/km h 。
2、假设警察出警的地点都是平台处。
3、假设警察接到通知后同时出警，且不考虑路面交通状况。
三、符号说明及一些符号的详细解释A 存储全市图信息的邻接矩阵 D 任意两路口节点间的最短距离矩阵X 01-规划矩阵ij a ,i j 两路口节点标号之间直达的距离 ij d 从i 路口到j 路口的最短距离 ij b 从i 号平台到j 号出口的最短距离ij x 取0或1，1ij x =表示第i 号平台去封锁j 号出口在本文中经常用到,i j ，通常表示路口的编号，但是在ij d ，ij b ，ij x 不再表示这个意思，i 表示第i 个交巡警平台，交巡警平台的标号与附件中给的略有不同，如第21个交巡警平台为附件中的标号为93的交巡警平台，本文的标号是按照程序的数据读取顺序来标注的，在此声明；j 表示第j 个出口，如：第5个出口对应于附件中的路口编号为203的出口。