Iteration final - SOLVER_EXECUTION
Sequence: 6
Timestamp: 2025-07-25 22:43:00

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

Response:
{
  "gurobipy": {
    "solver_type": "gurobipy",
    "execution_time": 0.1903209686279297,
    "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 9 rows, 27 columns and 81 nonzeros\nModel fingerprint: 0xfbd49f8d\nVariable types: 0 continuous, 27 integer (27 binary)\nCoefficient statistics:\n  Matrix range     [1e+00, 1e+00]\n  Objective range  [1e+00, 3e+00]\n  Bounds range     [1e+00, 1e+00]\n  RHS range        [1e+00, 2e+00]\nFound heuristic solution: objective 4.0000000\nPresolve time: 0.00s\nPresolved: 9 rows, 27 columns, 81 nonzeros\nVariable types: 0 continuous, 27 integer (27 binary)\n\nRoot relaxation: objective 6.000000e+00, 4 iterations, 0.00 seconds (0.00 work units)\n\n    Nodes    |    Current Node    |     Objective Bounds      |     Work\n Expl Unexpl |  Obj  Depth IntInf | Incumbent    BestBd   Gap | It/Node Time\n\n*    0     0               0       6.0000000    6.00000  0.00%     -    0s\n\nExplored 1 nodes (4 simplex iterations) in 0.00 seconds (0.00 work units)\nThread count was 32 (of 128 available processors)\n\nSolution count 2: 6 4 \n\nOptimal solution found (tolerance 1.00e-04)\nBest objective 6.000000000000e+00, best bound 6.000000000000e+00, gap 0.0000%\nOptimal value: 6.0\nResearcher 1 assigned to Institution 103 for Paper 201\nResearcher 2 assigned to Institution 103 for Paper 202\nResearcher 3 assigned to Institution 102 for Paper 203\n",
    "stderr": "",
    "status": "optimal",
    "optimal_value": 6.0,
    "error_message": null,
    "decision_variables": {},
    "retry_attempt": 4
  },
  "docplex": {
    "solver_type": "docplex",
    "execution_time": 0.03695368766784668,
    "return_code": 1,
    "stdout": "",
    "stderr": "  File \"/tmp/tmpaky4bdug.py\", line 29\n    x = mdl.binary_var_dict((a, i, p) for a in A for i in I for p in P, name=\"x\")\n                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nSyntaxError: Generator expression must be parenthesized\n",
    "status": "error",
    "optimal_value": null,
    "error_message": "  File \"/tmp/tmpaky4bdug.py\", line 29\n    x = mdl.binary_var_dict((a, i, p) for a in A for i in I for p in P, name=\"x\")\n                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nSyntaxError: Generator expression must be parenthesized\n",
    "decision_variables": {},
    "retry_attempt": 4
  },
  "pyomo": {
    "solver_type": "pyomo",
    "execution_time": 0.8249075412750244,
    "return_code": 1,
    "stdout": "WARNING: Initializing ordered Set A with a fundamentally unordered data source\n(type: set).  This WILL potentially lead to nondeterministic behavior in Pyomo\nWARNING: Initializing ordered Set I with a fundamentally unordered data source\n(type: set).  This WILL potentially lead to nondeterministic behavior in Pyomo\nWARNING: Initializing ordered Set P with a fundamentally unordered data source\n(type: set).  This WILL potentially lead to nondeterministic behavior in Pyomo\nERROR: Rule failed when generating expression for Objective objective with\nindex None: ValueError: Error retrieving immutable Param value (weights[(1,\n202)]):\n            The Param value is undefined and no default value is specified.\nERROR: Constructing component 'objective' from data=None failed:\n        ValueError: Error retrieving immutable Param value (weights[(1,\n        202)]):\n    \tThe Param value is undefined and no default value is specified.\n",
    "stderr": "Traceback (most recent call last):\n  File \"/tmp/tmpby3ehu4b.py\", line 79, in <module>\n    optimize_research_allocation()\n  File \"/tmp/tmpby3ehu4b.py\", line 46, in optimize_research_allocation\n    model.objective = pyo.Objective(rule=obj_rule, sense=pyo.maximize)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/block.py\", line 571, in __setattr__\n    self.add_component(name, val)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/block.py\", line 1101, in add_component\n    val.construct(data)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/objective.py\", line 336, in construct\n    ans = self._setitem_when_not_present(index, rule(block, index))\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/initializer.py\", line 485, in __call__\n    return self._fcn(parent)\n  File \"/tmp/tmpby3ehu4b.py\", line 45, in obj_rule\n    return sum(model.weights[a, p] * model.x[a, i, p] for a in model.A for i in model.I for p in model.P)\n  File \"/tmp/tmpby3ehu4b.py\", line 45, in <genexpr>\n    return sum(model.weights[a, p] * model.x[a, i, p] for a in model.A for i in model.I for p in model.P)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/param.py\", line 1012, in __getitem__\n    return super().__getitem__(args)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/indexed_component.py\", line 662, in __getitem__\n    return self._getitem_when_not_present(index)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/param.py\", line 627, in _getitem_when_not_present\n    raise ValueError(\nValueError: Error retrieving immutable Param value (weights[(1, 202)]):\n\tThe Param value is undefined and no default value is specified.\n",
    "status": "error",
    "optimal_value": null,
    "error_message": "Traceback (most recent call last):\n  File \"/tmp/tmpby3ehu4b.py\", line 79, in <module>\n    optimize_research_allocation()\n  File \"/tmp/tmpby3ehu4b.py\", line 46, in optimize_research_allocation\n    model.objective = pyo.Objective(rule=obj_rule, sense=pyo.maximize)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/block.py\", line 571, in __setattr__\n    self.add_component(name, val)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/block.py\", line 1101, in add_component\n    val.construct(data)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/objective.py\", line 336, in construct\n    ans = self._setitem_when_not_present(index, rule(block, index))\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/initializer.py\", line 485, in __call__\n    return self._fcn(parent)\n  File \"/tmp/tmpby3ehu4b.py\", line 45, in obj_rule\n    return sum(model.weights[a, p] * model.x[a, i, p] for a in model.A for i in model.I for p in model.P)\n  File \"/tmp/tmpby3ehu4b.py\", line 45, in <genexpr>\n    return sum(model.weights[a, p] * model.x[a, i, p] for a in model.A for i in model.I for p in model.P)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/param.py\", line 1012, in __getitem__\n    return super().__getitem__(args)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/indexed_component.py\", line 662, in __getitem__\n    return self._getitem_when_not_present(index)\n  File \"/dccstor/nl2opt/miniforge3/envs/nl2opt_optim/lib/python3.10/site-packages/pyomo/core/base/param.py\", line 627, in _getitem_when_not_present\n    raise ValueError(\nValueError: Error retrieving immutable Param value (weights[(1, 202)]):\n\tThe Param value is undefined and no default value is specified.\n",
    "decision_variables": {},
    "retry_attempt": 4
  }
}
