Iteration final - SOLVER_EXECUTION
Sequence: 6
Timestamp: 2025-07-25 22:27:52

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

Response:
{
  "gurobipy": {
    "solver_type": "gurobipy",
    "execution_time": 0.18555235862731934,
    "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 10 rows, 3 columns and 12 nonzeros\nModel fingerprint: 0x7e81d929\nCoefficient statistics:\n  Matrix range     [1e+00, 1e+00]\n  Objective range  [5e-01, 7e-01]\n  Bounds range     [0e+00, 0e+00]\n  RHS range        [1e+02, 1e+06]\nPresolve removed 10 rows and 3 columns\nPresolve time: 0.00s\nPresolve: All rows and columns removed\nIteration    Objective       Primal Inf.    Dual Inf.      Time\n       0    1.6500000e+05   0.000000e+00   0.000000e+00      0s\n\nSolved in 0 iterations and 0.00 seconds (0.00 work units)\nOptimal objective  1.650000000e+05\nOptimal value: 165000.0\nx[1] = 100000.000\nx[2] = 100000.000\nx[3] = 100000.000\n",
    "stderr": "",
    "status": "optimal",
    "optimal_value": 165000.0,
    "error_message": null,
    "decision_variables": {}
  },
  "docplex": {
    "solver_type": "docplex",
    "execution_time": 1.0620191097259521,
    "return_code": 1,
    "stdout": "",
    "stderr": "Traceback (most recent call last):\n  File \"/tmp/tmpgsltrs0t.py\", line 70, in <module>\n    election_campaign_optimization()\n  File \"/tmp/tmpgsltrs0t.py\", line 33, in election_campaign_optimization\n    objective = mdl.sum(turnout_per_dollar[i] * x[i] for i in safe_range)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/docplex/mp/model.py\", line 3342, in sum\n    return self._aggregator.sum(args)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/docplex/mp/aggregator.py\", line 198, in sum\n    sum_res = self._sum_with_iter(sum_args)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/docplex/mp/aggregator.py\", line 221, in _sum_with_iter\n    for item in args:\n  File \"/tmp/tmpgsltrs0t.py\", line 33, in <genexpr>\n    objective = mdl.sum(turnout_per_dollar[i] * x[i] for i in safe_range)\nKeyError: 0\n",
    "status": "error",
    "optimal_value": null,
    "error_message": "Traceback (most recent call last):\n  File \"/tmp/tmpgsltrs0t.py\", line 70, in <module>\n    election_campaign_optimization()\n  File \"/tmp/tmpgsltrs0t.py\", line 33, in election_campaign_optimization\n    objective = mdl.sum(turnout_per_dollar[i] * x[i] for i in safe_range)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/docplex/mp/model.py\", line 3342, in sum\n    return self._aggregator.sum(args)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/docplex/mp/aggregator.py\", line 198, in sum\n    sum_res = self._sum_with_iter(sum_args)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/docplex/mp/aggregator.py\", line 221, in _sum_with_iter\n    for item in args:\n  File \"/tmp/tmpgsltrs0t.py\", line 33, in <genexpr>\n    objective = mdl.sum(turnout_per_dollar[i] * x[i] for i in safe_range)\nKeyError: 0\n",
    "decision_variables": {}
  },
  "pyomo": {
    "solver_type": "pyomo",
    "execution_time": 0.8825922012329102,
    "return_code": 0,
    "stdout": "Read LP format model from file /tmp/tmpy70xgwog.pyomo.lp\nReading time = 0.00 seconds\nx1: 10 rows, 3 columns, 12 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 10 rows, 3 columns and 12 nonzeros\nModel fingerprint: 0x7e81d929\nCoefficient statistics:\n  Matrix range     [1e+00, 1e+00]\n  Objective range  [5e-01, 7e-01]\n  Bounds range     [0e+00, 0e+00]\n  RHS range        [1e+02, 1e+06]\nPresolve removed 10 rows and 3 columns\nPresolve time: 0.00s\nPresolve: All rows and columns removed\nIteration    Objective       Primal Inf.    Dual Inf.      Time\n       0    1.6500000e+05   0.000000e+00   0.000000e+00      0s\n\nSolved in 0 iterations and 0.00 seconds (0.00 work units)\nOptimal objective  1.650000000e+05\nOptimal solution found!\nOptimal value: 165000.0\n\nResource Allocation:\nCounty 1: $100000.00\nCounty 2: $100000.00\nCounty 3: $100000.00\n",
    "stderr": "",
    "status": "optimal",
    "optimal_value": 165000.0,
    "error_message": null,
    "decision_variables": {}
  }
}
