2018 XCSP3 competition: sequential solvers tracks: solvers results per benchmarks

Result page for benchmark
Rlfap/Rlfap-opt/
Rlfap-scen-01-opt_c18.xml

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General information on the benchmark

NameRlfap/Rlfap-opt/
Rlfap-scen-01-opt_c18.xml
MD5SUM2ee48e6c5f3b799813662dbb853aaebc
Bench CategoryCOP (optimization problem)
Best result obtained on this benchmarkSAT
Best value of the objective obtained on this benchmark16
Best CPU time to get the best result obtained on this benchmark2520.08
Satisfiable
(Un)Satisfiability was proved
Number of variables916
Number of constraints5548
Number of domains7
Minimum domain size6
Maximum domain size44
Distribution of domain sizes[{"size":6,"count":6},{"size":22,"count":36},{"size":24,"count":8},{"size":36,"count":360},{"size":42,"count":22},{"size":44,"count":484}]
Minimum variable degree2
Maximum variable degree62
Distribution of variable degrees[{"degree":2,"count":12},{"degree":3,"count":2},{"degree":4,"count":38},{"degree":5,"count":25},{"degree":6,"count":95},{"degree":7,"count":25},{"degree":8,"count":106},{"degree":9,"count":20},{"degree":10,"count":111},{"degree":11,"count":39},{"degree":12,"count":56},{"degree":13,"count":41},{"degree":14,"count":47},{"degree":15,"count":30},{"degree":16,"count":41},{"degree":17,"count":19},{"degree":18,"count":32},{"degree":19,"count":15},{"degree":20,"count":27},{"degree":21,"count":21},{"degree":22,"count":8},{"degree":23,"count":11},{"degree":24,"count":18},{"degree":25,"count":13},{"degree":26,"count":7},{"degree":27,"count":7},{"degree":28,"count":7},{"degree":29,"count":7},{"degree":30,"count":7},{"degree":31,"count":6},{"degree":32,"count":4},{"degree":33,"count":2},{"degree":35,"count":1},{"degree":36,"count":1},{"degree":37,"count":2},{"degree":38,"count":2},{"degree":39,"count":2},{"degree":40,"count":3},{"degree":43,"count":1},{"degree":44,"count":1},{"degree":45,"count":2},{"degree":55,"count":1},{"degree":62,"count":1}]
Minimum constraint arity2
Maximum constraint arity2
Distribution of constraint arities[{"arity":2,"count":5548}]
Number of extensional constraints0
Number of intensional constraints5548
Distribution of constraint types[{"type":"intension","count":5548}]
Optimization problemYES
Type of objectivemin NVALUES

Results of the different solvers on this benchmark

Solver NameTraceIDAnswerobjective functionCPU timeWall clock time
Choco-solver 4.0.7 seq (493a269) (complete)4292717SAT (TO)16 2400.12 2386.82
cosoco 1.12 (complete)4293558SAT (TO)16 2520.08 2520.01
Choco-solver 4.0.7b seq (e747e1e) (complete)4307011SAT (TO)16 2520.13 2505.72
Concrete 3.8-SuperNG 2018-06-13 (complete)4293557SAT (TO)16 2520.14 2470.95
Concrete 3.8 2018-06-13 (complete)4293556SAT (TO)16 2520.15 2471.28
Concrete 3.9.2-SuperNG (complete)4304310SAT (TO)16 2520.27 2464.31
Concrete 3.9.2 (complete)4304309SAT (TO)16 2520.36 2474.38
OscaR - Conflict Ordering with restarts 2018-07-02 (complete)4291864SAT (TO)46 2400.07 2364.63
OscaR - Conflict Ordering with restarts 2018-08-14 (complete)4308305SAT (TO)46 2520.07 2513.62
OscaR - Hybrid 2018-08-14 (complete)4308667SAT (TO)46 2520.1 2512.22
OscaR - Conflict Ordering with restarts 2018-08-17 (complete)4312041SAT (TO)48 2520.12 2512.91
Sat4j-CSP 2018-07-11 (complete)4291863? 1766.94 474.122
Mistral-2.0 2018-06-15 (complete)4291862? (TO) 2400.03 2399.9
PicatSAT 2018-08-14 (complete)4309827? (TO) 2519.86 2520.01
PicatSAT 2018-08-02 (complete)4303487? (TO) 2519.99 2520.01
PicatSAT 2018-06-15 (complete)4293559? (TO) 2520.1 2520.01
Mistral-2.0 2018-08-01 (complete)4304073? (TO) 2520.11 2520.01
OscaR - Hybrid 2018-07-02 (complete)4291866Wrong Opt.42 7.08842 2.87619

Additionnal information

This section presents information obtained from the best job displayed in the list (i.e. solvers whose names are not hidden).

objective function: 16
Solution found:
<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] x[680] x[681] x[682] x[683] x[684] x[685] x[686] x[687] x[688] x[689] x[690]
x[691] x[692] x[693] x[694] x[695] x[696] x[697] x[698] x[699] x[700] x[701] x[702] x[703] x[704] x[705] x[706] x[707] x[708] x[709] x[710]
x[711] x[712] x[713] x[714] x[715] x[716] x[717] x[718] x[719] x[720] x[721] x[722] x[723] x[724] x[725] x[726] x[727] x[728] x[729] x[730]
x[731] x[732] x[733] x[734] x[735] x[736] x[737] x[738] x[739] x[740] x[741] x[742] x[743] x[744] x[745] x[746] x[747] x[748] x[749] x[750]
x[751] x[752] x[753] x[754] x[755] x[756] x[757] x[758] x[759] x[760] x[761] x[762] x[763] x[764] x[765] x[766] x[767] x[768] x[769] x[770]
x[771] x[772] x[773] x[774] x[775] x[776] x[777] x[778] x[779] x[780] x[781] x[782] x[783] x[784] x[785] x[786] x[787] x[788] x[789] x[790]
x[791] x[792] x[793] x[794] x[795] x[796] x[797] x[798] x[799] x[800] x[801] x[802] x[803] x[804] x[805] x[806] x[807] x[808] x[809] x[810]
x[811] x[812] x[813] x[814] x[815] x[816] x[817] x[818] x[819] x[820] x[821] x[822] x[823] x[824] x[825] x[826] x[827] x[828] x[829] x[830]
x[831] x[832] x[833] x[834] x[835] x[836] x[837] x[838] x[839] x[840] x[841] x[842] x[843] x[844] x[845] x[846] x[847] x[848] x[849] x[850]
x[851] x[852] x[853] x[854] x[855] x[856] x[857] x[858] x[859] x[860] x[861] x[862] x[863] x[864] x[865] x[866] x[867] x[868] x[869] x[870]
x[871] x[872] x[873] x[874] x[875] x[876] x[877] x[878] x[879] x[880] x[881] x[882] x[883] x[884] x[885] x[886] x[887] x[888] x[889] x[890]
x[891] x[892] x[893] x[894] x[895] x[896] x[897] x[898] x[899] x[900] x[901] x[902] x[903] x[904] x[905] x[906] x[907] x[908] x[909] x[910]
x[911] x[912] x[913] x[914] x[915] </list> <values>16 254 380 142 16 254 254 16 142 380 254 16 30 268 30 268 764 526 352 114 100 338 100 338
268 30 352 114 764 526 30 268 30 268 380 142 352 114 442 680 114 352 30 268 380 142 442 680 338 100 254 16 268 30 254 16 268 30 100 338 352
114 114 352 30 268 380 142 16 254 352 114 16 254 352 114 30 268 254 16 100 338 16 254 380 142 352 114 352 114 338 100 254 16 680 442 142 380
254 16 526 764 30 268 352 114 268 30 100 338 680 442 254 16 268 30 764 526 338 100 16 254 352 114 30 268 142 380 254 16 338 100 442 680 30
268 100 338 680 442 478 240 16 254 16 254 442 680 16 254 114 352 764 526 100 338 16 254 100 338 442 680 114 352 254 16 142 380 338 100 338
100 268 30 268 30 338 100 142 380 30 268 16 254 114 352 30 268 142 380 268 30 142 380 338 100 254 16 268 30 268 30 680 442 100 338 442 680
680 442 680 442 100 338 764 526 442 680 16 254 100 338 16 254 16 254 338 100 338 100 100 338 142 380 30 268 352 114 764 526 114 352 114 352
142 380 338 100 338 100 142 380 680 442 338 100 254 16 16 254 16 254 254 16 680 442 338 100 442 680 442 680 764 526 764 526 338 100 100 338
380 142 380 142 16 254 16 254 114 352 254 16 380 142 268 30 16 254 16 254 526 764 338 100 680 442 16 254 380 142 442 680 442 680 16 254 352
114 16 254 526 764 526 764 100 338 442 680 114 352 380 142 764 526 352 114 254 16 30 268 114 352 114 352 380 142 764 526 338 100 338 100 442
680 268 30 30 268 352 114 100 338 380 142 442 680 338 100 526 764 16 254 142 380 114 352 114 352 352 114 338 100 268 30 100 338 142 380 254
16 30 268 30 268 764 526 16 254 268 30 30 268 352 114 142 380 16 254 338 100 30 268 338 100 380 142 680 442 30 268 142 380 100 338 268 30
142 380 100 338 442 680 680 442 30 268 114 352 680 442 100 338 100 338 100 338 254 16 114 352 380 142 254 16 16 254 268 30 380 142 338 100
114 352 100 338 268 30 338 100 338 100 100 338 142 380 680 442 380 142 442 680 114 352 254 16 254 16 268 30 114 352 268 30 16 254 254 16 30
268 268 30 764 526 680 442 100 338 380 142 764 526 30 268 254 16 268 30 100 338 142 380 30 268 338 100 352 114 100 338 16 254 268 30 100 338
254 16 30 268 254 16 142 380 114 352 114 352 338 100 142 380 268 30 114 352 442 680 114 352 442 680 380 142 100 338 30 268 380 142 352 114
100 338 352 114 16 254 352 114 16 254 268 30 352 114 142 380 114 352 442 680 100 338 338 100 30 268 338 100 268 30 30 268 30 268 338 100 254
16 268 30 114 352 114 352 30 268 268 30 30 268 30 268 100 338 338 100 338 100 30 268 268 30 380 142 380 142 352 114 100 338 142 380 268 30
764 526 254 16 114 352 254 16 30 268 338 100 764 526 16 254 114 352 254 16 30 268 268 30 30 268 254 16 764 526 100 338 268 30 338 100 268 30
338 100 114 352 30 268 100 338 268 30 254 16 338 100 16 254 16 254 16 254 338 100 30 268 100 338 100 338 338 100 268 30 764 526 380 142 16
254 442 680 268 30 268 30 268 30 442 680 338 100 338 100 30 268 338 100 680 442 268 30 268 30 338 100 30 268 30 268 338 100 114 352 30 268
338 100 100 338 352 114 268 30 380 142 268 30 30 268 100 338 338 100 764 526 254 16 254 16 338 100 114 352 268 30 338 100 114 352 268 30 100
338 30 268 100 338 114 352 114 352 338 100 268 30 142 380 338 100 114 352 30 268 142 380 352 114 30 268 380 142 680 442 338 100 352 114 100
338 16 254 100 338 268 30 16 254 268 30 338 100 380 142 254 16 268 30 442 680 100 338 352 114 254 16 114 352 114 352 16 254 268 30 30 268
352 114 380 142 352 114 100 338 114 352 30 268 100 338 338 100 338 100 380 142 352 114 30 268 338 100 114 352 268 30 100 338 30 268 254 16
254 16 338 100 764 526 268 30 30 268 30 268 </values> </instantiation>