Iteration 0 - OR_EXPERT
Sequence: 1
Timestamp: 2025-07-27 22:47:35

Prompt:
You are an Operations Research (OR) expert focused ONLY on optimization modeling. Your role is to analyze the business domain and design LINEAR optimization problems without involving database design decisions.

CRITICAL MATHEMATICAL CONSTRAINTS FOR LINEAR/MIXED-INTEGER PROGRAMMING:
- The optimization problem MUST be either Linear Programming (LP) or Mixed-Integer Programming (MIP)
- Objective function MUST be linear: minimize/maximize ∑(coefficient × variable)
- All constraints MUST be linear: ∑(coefficient × variable) ≤/≥/= constant
- Decision variables can be continuous (LP) or mixed continuous/integer (MIP)
- NO variable products, divisions, or other nonlinear relationships
- Design business scenarios that naturally lead to linear mathematical formulations
- Generate between 2 and 20 constraints for optimization feasibility

YOUR SCOPE: Focus exclusively on optimization modeling and understanding current schema-to-optimization mapping. Do NOT propose database changes.
ROW COUNT AWARENESS: Be aware that data engineer will apply 3-row minimum rule - tables unable to generate sufficient meaningful rows will be moved to business_configuration_logic.json.

CRITICAL: Respond with ONLY a valid JSON object. No explanations, no markdown, no extra text.

Database: inn_1

```sql
CREATE TABLE Rooms (
  RoomId TEXT,
  roomName TEXT,
  beds NUMBER,
  bedType TEXT,
  maxOccupancy NUMBER,
  basePrice NUMBER,
  decor TEXT
);
```

```sql
CREATE TABLE Reservations (
  Code NUMBER,
  Room TEXT,
  CheckIn TEXT,
  CheckOut TEXT,
  Rate NUMBER,
  LastName TEXT,
  FirstName TEXT,
  Adults NUMBER,
  Kids NUMBER
);
```



Current Business Configuration Logic: {} (initially empty)

TASK: Design a realistic LINEAR optimization problem and analyze how it maps to the current schema.

JSON STRUCTURE REQUIRED:

{
  "database_id": "inn_1",
  "iteration": 0,
  "business_context": "Describe the realistic business scenario that leads to linear optimization (avoid scenarios requiring nonlinear relationships)",
  "optimization_problem_description": "Detailed description of what needs to be optimized using linear objective functions and constraints",
  "optimization_formulation": {
    "objective": "minimize/maximize specific_linear_metric with clear definition (sum of weighted variables only)",
    "decision_variables": "What linear variables can be controlled/decided (continuous or integer)",
    "constraints": "What linear limitations must be respected (no variable products or divisions) - design 2 to 20 constraints"
  },
  
  "current_optimization_to_schema_mapping": {
    "objective_coefficients": {
      "coefficient_name[indices]": {
        "currently_mapped_to": "table.column OR business_configuration_logic.key OR missing",
        "mapping_adequacy": "good/missing/redundant/partial/inaccurate",
        "description": "what this coefficient represents in the optimization model"
      }
    },
    "constraint_bounds": {
      "constraint_name[indices]": {
        "currently_mapped_to": "table.column OR business_configuration_logic.key OR missing", 
        "mapping_adequacy": "good/missing/redundant/partial/inaccurate",
        "description": "what this constraint bound represents"
      }
    },
    "decision_variables": {
      "variable_name[indices]": {
        "currently_mapped_to": "table.column OR business_configuration_logic.key OR missing",
        "mapping_adequacy": "good/missing/redundant/partial/inaccurate", 
        "description": "what this decision variable represents",
        "variable_type": "continuous/integer/binary"
      }
    }
  },
  
  "missing_optimization_requirements": [
    "List what data/parameters are needed for complete linear optimization model"
  ],
  
  "iteration_status": {
    "complete": false,
    "confidence": "low/medium/high",
    "next_focus": "What optimization aspects need refinement"
  }
}

Response:
{
  "database_id": "inn_1",
  "iteration": 0,
  "business_context": "The inn wants to maximize its revenue by optimizing room pricing while considering occupancy constraints and room availability.",
  "optimization_problem_description": "Maximize the total revenue from room bookings by adjusting room rates, ensuring that the occupancy does not exceed the maximum capacity of each room and that all reservations are honored.",
  "optimization_formulation": {
    "objective": "maximize total_revenue = \u2211(Rate[Code] \u00d7 (CheckOut[Code] - CheckIn[Code]))",
    "decision_variables": "Rate[Code] for each reservation Code, continuous",
    "constraints": [
      "\u2211(Adults[Code] + Kids[Code]) \u2264 maxOccupancy[RoomId] for each RoomId",
      "Rate[Code] \u2265 basePrice[RoomId] for each reservation Code"
    ]
  },
  "current_optimization_to_schema_mapping": {
    "objective_coefficients": {
      "Rate[Code]": {
        "currently_mapped_to": "Reservations.Rate",
        "mapping_adequacy": "good",
        "description": "The rate charged for each reservation, which is a decision variable in the optimization model"
      }
    },
    "constraint_bounds": {
      "maxOccupancy[RoomId]": {
        "currently_mapped_to": "Rooms.maxOccupancy",
        "mapping_adequacy": "good",
        "description": "The maximum number of people that can occupy a room"
      },
      "basePrice[RoomId]": {
        "currently_mapped_to": "Rooms.basePrice",
        "mapping_adequacy": "good",
        "description": "The minimum rate that can be charged for a room"
      }
    },
    "decision_variables": {
      "Rate[Code]": {
        "currently_mapped_to": "Reservations.Rate",
        "mapping_adequacy": "good",
        "description": "The rate for each reservation that can be adjusted to maximize revenue",
        "variable_type": "continuous"
      }
    }
  },
  "missing_optimization_requirements": [
    "CheckIn and CheckOut dates need to be converted to numerical values representing the length of stay",
    "Ensure that all reservations are mapped to existing rooms"
  ],
  "iteration_status": {
    "complete": false,
    "confidence": "medium",
    "next_focus": "Refine the conversion of CheckIn and CheckOut dates to numerical values and ensure all reservations are valid"
  }
}
