| Name | Rlfap/Rlfap-opt/ Rlfap-scen-04-opt_c18.xml |
| MD5SUM | 78811932529a67bdc61c23a432ac663c |
| Bench Category | COP (optimization problem) |
| Best result obtained on this benchmark | OPT |
| Best value of the objective obtained on this benchmark | 46 |
| Best CPU time to get the best result obtained on this benchmark | 130.9 |
| Satisfiable | |
| (Un)Satisfiability was proved | |
| Number of variables | 680 |
| Number of constraints | 3968 |
| Number of domains | 5 |
| Minimum domain size | 6 |
| Maximum domain size | 44 |
| Distribution of domain sizes | [{"size":6,"count":2},{"size":22,"count":10},{"size":24,"count":4},{"size":36,"count":336},{"size":44,"count":328}] |
| Minimum variable degree | 3 |
| Maximum variable degree | 64 |
| Distribution of variable degrees | [{"degree":3,"count":1},{"degree":4,"count":16},{"degree":5,"count":22},{"degree":6,"count":62},{"degree":7,"count":42},{"degree":8,"count":62},{"degree":9,"count":40},{"degree":10,"count":55},{"degree":11,"count":55},{"degree":12,"count":47},{"degree":13,"count":41},{"degree":14,"count":26},{"degree":15,"count":25},{"degree":16,"count":24},{"degree":17,"count":19},{"degree":18,"count":19},{"degree":19,"count":19},{"degree":20,"count":10},{"degree":21,"count":10},{"degree":22,"count":17},{"degree":23,"count":8},{"degree":24,"count":6},{"degree":25,"count":10},{"degree":26,"count":9},{"degree":27,"count":10},{"degree":28,"count":3},{"degree":29,"count":2},{"degree":31,"count":4},{"degree":32,"count":3},{"degree":33,"count":1},{"degree":35,"count":1},{"degree":36,"count":1},{"degree":40,"count":3},{"degree":41,"count":1},{"degree":44,"count":2},{"degree":45,"count":1},{"degree":47,"count":1},{"degree":57,"count":1},{"degree":64,"count":1}] |
| Minimum constraint arity | 2 |
| Maximum constraint arity | 280 |
| Distribution of constraint arities | [{"arity":2,"count":3967},{"arity":280,"count":1}] |
| Number of extensional constraints | 0 |
| Number of intensional constraints | 3967 |
| Distribution of constraint types | [{"type":"intension","count":3967},{"type":"instantiation","count":1}] |
| Optimization problem | YES |
| Type of objective | min NVALUES |
| Solver Name | TraceID | Answer | objective function | CPU time | Wall clock time |
|---|---|---|---|---|---|
| OscaR - Parallel with EPS 2018-07-02 (complete) | 4291945 | OPT | 46 | 21.1121 | 5.77411 |
| Choco-solver 4.0.7b par (e747e1e) (complete) | 4297870 | OPT | 46 | 130.9 | 19.8691 |
| OscaR - Parallel with EPS 2018-08-14 (complete) | 4309226 | ? (TO) | 11478.3 | 2520.35 |
This section presents information obtained from the best job displayed in the list (i.e. solvers whose names are not hidden).
objective function: 46<instantiation> <list> x[0] x[1] x[2] x[3] x[4] x[5] x[6] x[7] x[8] x[9] x[10] x[11] x[12] x[13] x[14] x[15] x[16] x[17] x[18] x[19] x[20] x[21] x[22] x[23] x[24] x[25] x[26] x[27] x[28] x[29] x[30] x[31] x[32] x[33] x[34] x[35] x[36] x[37] x[38] x[39] x[40] x[41] x[42] x[43] x[44] x[45] x[46] x[47] x[48] x[49] x[50] x[51] x[52] x[53] x[54] x[55] x[56] x[57] x[58] x[59] x[60] x[61] x[62] x[63] x[64] x[65] x[66] x[67] x[68] x[69] x[70] x[71] x[72] x[73] x[74] x[75] x[76] x[77] x[78] x[79] x[80] x[81] x[82] x[83] x[84] x[85] x[86] x[87] x[88] x[89] x[90] x[91] x[92] x[93] x[94] x[95] x[96] x[97] x[98] x[99] x[100] x[101] x[102] x[103] x[104] x[105] x[106] x[107] x[108] x[109] x[110] x[111] x[112] x[113] x[114] x[115] x[116] x[117] x[118] x[119] x[120] x[121] x[122] x[123] x[124] x[125] x[126] x[127] x[128] x[129] x[130] x[131] x[132] x[133] x[134] x[135] x[136] x[137] x[138] x[139] x[140] x[141] x[142] x[143] x[144] x[145] x[146] x[147] x[148] x[149] x[150] x[151] x[152] x[153] x[154] x[155] x[156] x[157] x[158] x[159] x[160] x[161] x[162] x[163] x[164] x[165] x[166] x[167] x[168] x[169] x[170] x[171] x[172] x[173] x[174] x[175] x[176] x[177] x[178] x[179] x[180] x[181] x[182] x[183] x[184] x[185] x[186] x[187] x[188] x[189] x[190] x[191] x[192] x[193] x[194] x[195] x[196] x[197] x[198] x[199] x[200] x[201] x[202] x[203] x[204] x[205] x[206] x[207] x[208] x[209] x[210] x[211] x[212] x[213] x[214] x[215] x[216] x[217] x[218] x[219] x[220] x[221] x[222] x[223] x[224] x[225] x[226] x[227] x[228] x[229] x[230] x[231] x[232] x[233] x[234] x[235] x[236] x[237] x[238] x[239] x[240] x[241] x[242] x[243] x[244] x[245] x[246] x[247] x[248] x[249] x[250] x[251] x[252] x[253] x[254] x[255] x[256] x[257] x[258] x[259] x[260] x[261] x[262] x[263] x[264] x[265] x[266] x[267] x[268] x[269] x[270] x[271] x[272] x[273] x[274] x[275] x[276] x[277] x[278] x[279] x[280] x[281] x[282] x[283] x[284] x[285] x[286] x[287] x[288] x[289] x[290] x[291] x[292] x[293] x[294] x[295] x[296] x[297] x[298] x[299] x[300] x[301] x[302] x[303] x[304] x[305] x[306] x[307] x[308] x[309] x[310] x[311] x[312] x[313] x[314] x[315] x[316] x[317] x[318] x[319] x[320] x[321] x[322] x[323] x[324] x[325] x[326] x[327] x[328] x[329] x[330] x[331] x[332] x[333] x[334] x[335] x[336] x[337] x[338] x[339] x[340] x[341] x[342] x[343] x[344] x[345] x[346] x[347] x[348] x[349] x[350] x[351] x[352] x[353] x[354] x[355] x[356] x[357] x[358] x[359] x[360] x[361] x[362] x[363] x[364] x[365] x[366] x[367] x[368] x[369] x[370] x[371] x[372] x[373] x[374] x[375] x[376] x[377] x[378] x[379] x[380] x[381] x[382] x[383] x[384] x[385] x[386] x[387] x[388] x[389] x[390] x[391] x[392] x[393] x[394] x[395] x[396] x[397] x[398] x[399] x[400] x[401] x[402] x[403] x[404] x[405] x[406] x[407] x[408] x[409] x[410] x[411] x[412] x[413] x[414] x[415] x[416] x[417] x[418] x[419] x[420] x[421] x[422] x[423] x[424] x[425] x[426] x[427] x[428] x[429] x[430] x[431] x[432] x[433] x[434] x[435] x[436] x[437] x[438] x[439] x[440] x[441] x[442] x[443] x[444] x[445] x[446] x[447] x[448] x[449] x[450] x[451] x[452] x[453] x[454] x[455] x[456] x[457] x[458] x[459] x[460] x[461] x[462] x[463] x[464] x[465] x[466] x[467] x[468] x[469] x[470] x[471] x[472] x[473] x[474] x[475] x[476] x[477] x[478] x[479] x[480] x[481] x[482] x[483] x[484] x[485] x[486] x[487] x[488] x[489] x[490] x[491] x[492] x[493] x[494] x[495] x[496] x[497] x[498] x[499] x[500] x[501] x[502] x[503] x[504] x[505] x[506] x[507] x[508] x[509] x[510] x[511] x[512] x[513] x[514] x[515] x[516] x[517] x[518] x[519] x[520] x[521] x[522] x[523] x[524] x[525] x[526] x[527] x[528] x[529] x[530] x[531] x[532] x[533] x[534] x[535] x[536] x[537] x[538] x[539] x[540] x[541] x[542] x[543] x[544] x[545] x[546] x[547] x[548] x[549] x[550] x[551] x[552] x[553] x[554] x[555] x[556] x[557] x[558] x[559] x[560] x[561] x[562] x[563] x[564] x[565] x[566] x[567] x[568] x[569] x[570] x[571] x[572] x[573] x[574] x[575] x[576] x[577] x[578] x[579] x[580] x[581] x[582] x[583] x[584] x[585] x[586] x[587] x[588] x[589] x[590] x[591] x[592] x[593] x[594] x[595] x[596] x[597] x[598] x[599] x[600] x[601] x[602] x[603] x[604] x[605] x[606] x[607] x[608] x[609] x[610] x[611] x[612] x[613] x[614] x[615] x[616] x[617] x[618] x[619] x[620] x[621] x[622] x[623] x[624] x[625] x[626] x[627] x[628] x[629] x[630] x[631] x[632] x[633] x[634] x[635] x[636] x[637] x[638] x[639] x[640] x[641] x[642] x[643] x[644] x[645] x[646] x[647] x[648] x[649] x[650] x[651] x[652] x[653] x[654] x[655] x[656] x[657] x[658] x[659] x[660] x[661] x[662] x[663] x[664] x[665] x[666] x[667] x[668] x[669] x[670] x[671] x[672] x[673] x[674] x[675] x[676] x[677] x[678] x[679] </list> <values> 708 470 310 72 750 512 16 254 16 254 338 100 128 366 750 512 156 394 394 156 778 540 442 680 16 254 652 414 526 764 296 58 554 792 128 366 30 268 30 268 708 470 156 394 652 414 86 324 394 156 30 268 778 540 72 310 156 394 156 394 540 778 142 380 394 156 722 484 554 792 296 58 652 414 554 792 554 792 142 380 114 352 142 380 44 282 652 414 526 764 296 58 156 394 86 324 470 708 338 100 526 764 652 414 296 58 526 764 470 708 86 324 324 86 792 554 268 30 142 380 764 526 114 352 72 310 792 554 428 666 764 526 652 414 58 296 310 72 792 554 72 310 72 310 498 736 792 554 554 792 394 156 736 498 442 680 512 750 170 408 554 792 30 268 540 778 380 142 44 282 456 694 792 554 394 156 708 470 484 722 666 428 310 72 394 156 254 16 156 394 156 394 380 142 366 128 750 512 792 554 512 750 792 554 540 778 540 778 394 156 156 394 456 694 72 310 44 282 58 296 540 778 282 44 380 142 498 736 366 128 428 666 764 526 282 44 750 512 694 456 778 540 540 778 44 282 366 128 338 100 428 666 296 58 694 456 128 366 778 540 366 128 708 470 442 680 282 44 456 694 380 142 540 778 380 142 540 778 680 442 338 100 114 352 442 680 750 512 666 428 778 540 156 394 652 414 778 540 44 282 352 114 540 778 282 44 142 380 470 708 310 72 778 540 456 694 540 778 484 722 540 778 708 470 540 778 540 778 680 442 72 310 380 142 128 366 380 142 380 142 722 484 296 58 366 128 380 142 512 750 708 470 792 554 338 100 414 652 338 100 310 72 58 296 156 394 666 428 380 142 456 694 296 58 366 128 142 380 694 456 338 100 778 540 44 282 428 666 722 484 792 554 442 680 554 792 694 456 764 526 394 156 792 554 764 526 128 366 380 142 526 764 540 778 778 540 114 352 680 442 540 778 554 792 142 380 540 778 484 722 30 268 142 380 778 540 498 736 366 128 268 30 666 428 44 282 428 666 128 366 268 30 352 114 44 282 86 324 352 114 512 750 470 708 792 554 338 100 16 254 394 156 394 156 540 778 72 310 142 380 540 778 680 442 498 736 128 366 778 540 114 352 498 736 100 338 722 484 72 310 156 394 72 310 72 310 708 470 394 156 792 554 778 540 540 778 540 778 764 526 540 778 310 72 666 428 792 554 44 282 72 310 722 484 296 58 142 380 540 778 442 680 540 778 310 72 44 282 540 778 666 428 324 86 680 442 394 156 680 442 282 44 282 44 72 310 58 296 778 540 380 142 540 778 708 470 380 142 708 470 778 540 540 778 456 694 142 380 282 44 540 778 142 380 540 778 338 100 680 442 778 540 324 86 512 750 16 254 254 16 554 792 142 380 540 778 554 792 296 58 792 554 296 58 484 722 498 736 778 540 792 554 442 680 380 142 442 680 156 394 554 792 142 380 778 540 540 778 128 366 128 366 282 44 708 470 470 708 540 778 114 352 30 268 380 142 72 310 736 498 86 324 268 30 268 30 540 778 156 394 </values> </instantiation>