Iteration final - SOLVER_EXECUTION
Sequence: 8
Timestamp: 2025-07-25 22:34:17

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

Response:
{
  "gurobipy": {
    "solver_type": "gurobipy",
    "execution_time": 0.16716766357421875,
    "return_code": 1,
    "stdout": "Restricted license - for non-production use only - expires 2026-11-23\n",
    "stderr": "Traceback (most recent call last):\n  File \"/tmp/tmp36qruidr.py\", line 62, in <module>\n    climbing_assignment_optimization()\n  File \"/tmp/tmp36qruidr.py\", line 35, in climbing_assignment_optimization\n    model.setObjective(gp.quicksum(points[i, j] * x[i, j] for i in climber_ids for j in mountain_ids), GRB.MAXIMIZE)\n  File \"src/gurobipy/_helpers.pyx\", line 41, in gurobipy._helpers.quicksum\n  File \"/tmp/tmp36qruidr.py\", line 35, in <genexpr>\n    model.setObjective(gp.quicksum(points[i, j] * x[i, j] for i in climber_ids for j in mountain_ids), GRB.MAXIMIZE)\nKeyError: (1, 2)\n",
    "status": "error",
    "optimal_value": null,
    "error_message": "Traceback (most recent call last):\n  File \"/tmp/tmp36qruidr.py\", line 62, in <module>\n    climbing_assignment_optimization()\n  File \"/tmp/tmp36qruidr.py\", line 35, in climbing_assignment_optimization\n    model.setObjective(gp.quicksum(points[i, j] * x[i, j] for i in climber_ids for j in mountain_ids), GRB.MAXIMIZE)\n  File \"src/gurobipy/_helpers.pyx\", line 41, in gurobipy._helpers.quicksum\n  File \"/tmp/tmp36qruidr.py\", line 35, in <genexpr>\n    model.setObjective(gp.quicksum(points[i, j] * x[i, j] for i in climber_ids for j in mountain_ids), GRB.MAXIMIZE)\nKeyError: (1, 2)\n",
    "decision_variables": {},
    "retry_attempt": 1
  },
  "docplex": {
    "solver_type": "docplex",
    "execution_time": 1.060877799987793,
    "return_code": 0,
    "stdout": "Optimal value: 60.0\nClimber 1 assigned to Mountain 1\nClimber 2 assigned to Mountain 2\nClimber 3 assigned to Mountain 3\n",
    "stderr": "",
    "status": "optimal",
    "optimal_value": 60.0,
    "error_message": null,
    "decision_variables": {},
    "retry_attempt": 1
  },
  "pyomo": {
    "solver_type": "pyomo",
    "execution_time": 0.8639533519744873,
    "return_code": 0,
    "stdout": "Read LP format model from file /tmp/tmpo43ty6s5.pyomo.lp\nReading time = 0.00 seconds\nx1: 4 rows, 9 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 4 rows, 9 columns and 12 nonzeros\nModel fingerprint: 0xc22592d4\nVariable types: 0 continuous, 9 integer (9 binary)\nCoefficient statistics:\n  Matrix range     [1e+00, 2e+01]\n  Objective range  [1e+01, 3e+01]\n  Bounds range     [1e+00, 1e+00]\n  RHS range        [1e+00, 1e+02]\nFound heuristic solution: objective 60.0000000\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 1: 60 \n\nOptimal solution found (tolerance 1.00e-02)\nBest objective 6.000000000000e+01, best bound 6.000000000000e+01, gap 0.0000%\nOptimal value: 60.0\n",
    "stderr": "",
    "status": "optimal",
    "optimal_value": 60.0,
    "error_message": null,
    "decision_variables": {},
    "retry_attempt": 1
  }
}
