Iteration final - SOLVER_EXECUTION
Sequence: 6
Timestamp: 2025-07-25 22:25:45

Prompt:
Generated solver codes with templates and executed them with retry logic

Response:
{
  "gurobipy": {
    "solver_type": "gurobipy",
    "execution_time": 0.1912391185760498,
    "return_code": 0,
    "stdout": "Restricted license - for non-production use only - expires 2026-11-23\nGurobi Optimizer version 12.0.2 build v12.0.2rc0 (linux64 - \"Red Hat Enterprise Linux 9.4 (Plow)\")\n\nCPU model: AMD EPYC 7513 32-Core Processor, instruction set [SSE2|AVX|AVX2]\nThread count: 64 physical cores, 128 logical processors, using up to 32 threads\n\nOptimize a model with 8 rows, 15 columns and 30 nonzeros\nModel fingerprint: 0xdfa6f29e\nVariable types: 0 continuous, 15 integer (15 binary)\nCoefficient statistics:\n  Matrix range     [1e+00, 1e+00]\n  Objective range  [1e+04, 3e+04]\n  Bounds range     [1e+00, 1e+00]\n  RHS range        [2e+00, 3e+04]\nFound heuristic solution: objective 150000.00000\nPresolve removed 8 rows and 15 columns\nPresolve time: 0.00s\nPresolve: All rows and columns removed\n\nExplored 0 nodes (0 simplex iterations) in 0.00 seconds (0.00 work units)\nThread count was 1 (of 128 available processors)\n\nSolution count 2: 250000 150000 \n\nOptimal solution found (tolerance 1.00e-04)\nBest objective 2.500000000000e+05, best bound 2.500000000000e+05, gap 0.0000%\nOptimal value: 250000.0\nSinger 0 assigned to stadium 1: 1\nSinger 0 assigned to stadium 2: 1\nSinger 1 assigned to stadium 1: 1\nSinger 1 assigned to stadium 2: 1\nSinger 2 assigned to stadium 1: 1\nSinger 2 assigned to stadium 2: 1\nSinger 3 assigned to stadium 1: 1\nSinger 3 assigned to stadium 2: 1\nSinger 4 assigned to stadium 1: 1\nSinger 4 assigned to stadium 2: 1\n",
    "stderr": "",
    "status": "optimal",
    "optimal_value": 250000.0,
    "error_message": null,
    "decision_variables": {}
  },
  "docplex": {
    "solver_type": "docplex",
    "execution_time": 1.4126253128051758,
    "return_code": 0,
    "stdout": "Optimal value: 150000.0\nSinger 0 assigned to stadium 1: 1\nSinger 0 assigned to stadium 2: 1\nSinger 1 assigned to stadium 1: 1\nSinger 1 assigned to stadium 2: 1\nSinger 2 assigned to stadium 1: 1\nSinger 2 assigned to stadium 2: 1\n",
    "stderr": "",
    "status": "optimal",
    "optimal_value": 150000.0,
    "error_message": null,
    "decision_variables": {}
  },
  "pyomo": {
    "solver_type": "pyomo",
    "execution_time": 0.9933328628540039,
    "return_code": 0,
    "stdout": "Read LP format model from file /tmp/tmp844v6vgh.pyomo.lp\nReading time = 0.00 seconds\nx1: 8 rows, 15 columns, 30 nonzeros\nSet parameter TimeLimit to value 300\nSet parameter MIPGap to value 0.01\nGurobi Optimizer version 12.0.2 build v12.0.2rc0 (linux64 - \"Red Hat Enterprise Linux 9.4 (Plow)\")\n\nCPU model: AMD EPYC 7513 32-Core Processor, instruction set [SSE2|AVX|AVX2]\nThread count: 64 physical cores, 128 logical processors, using up to 32 threads\n\nNon-default parameters:\nTimeLimit  300\nMIPGap  0.01\n\nOptimize a model with 8 rows, 15 columns and 30 nonzeros\nModel fingerprint: 0xdfa6f29e\nVariable types: 0 continuous, 15 integer (15 binary)\nCoefficient statistics:\n  Matrix range     [1e+00, 1e+00]\n  Objective range  [1e+04, 3e+04]\n  Bounds range     [1e+00, 1e+00]\n  RHS range        [2e+00, 3e+04]\nFound heuristic solution: objective 150000.00000\nPresolve removed 8 rows and 15 columns\nPresolve time: 0.00s\nPresolve: All rows and columns removed\n\nExplored 0 nodes (0 simplex iterations) in 0.00 seconds (0.00 work units)\nThread count was 1 (of 128 available processors)\n\nSolution count 2: 250000 150000 \n\nOptimal solution found (tolerance 1.00e-02)\nBest objective 2.500000000000e+05, best bound 2.500000000000e+05, gap 0.0000%\nOptimal solution found!\nOptimal value: 250000.0\n\nVariable values:\nSinger 1 assigned to Stadium 2\nSinger 1 assigned to Stadium 3\nSinger 2 assigned to Stadium 2\nSinger 2 assigned to Stadium 3\nSinger 3 assigned to Stadium 2\nSinger 3 assigned to Stadium 3\nSinger 4 assigned to Stadium 2\nSinger 4 assigned to Stadium 3\nSinger 5 assigned to Stadium 2\nSinger 5 assigned to Stadium 3\n",
    "stderr": "",
    "status": "optimal",
    "optimal_value": 250000.0,
    "error_message": null,
    "decision_variables": {}
  }
}
