Please generate a unique JSON object suitable for automating the programming task testing platform, strictly in the following format:
    {
  "Title": "Task Name",
  "Task Description": "Description of the task.",
  "Function Signature": "def function_name(parameters) -> return_type:",
  "Solve": "",
  "Input": "Description of the input parameters.",
  "Output": "Description of the expected output.",
  "Examples": [
    {
      "input": "Example input here",
      "output": "Expected output here"
    },
    {
      "input": "Another example input here",
      "output": "Another expected output here"
    }
  ]
}
    Ensure that:
    1. The task includes dynamic programming with constraints.
    2. The JSON follows this exact structure and does not include any additional text or variations.
    3. The task should be complex and unique, avoiding direct copying from common platforms like LeetCode or similar sources.
    4. The solution must not use any imports in the code (i.e., no import statements).
    5. The 'Solve' section must remain empty.
    6. Ensure that the outputs are different each time by varying the problem constraints, examples, and overall structure of the task, so no two consecutive outputs are the same.
    7. Include a unique aspect in each generated task, such as a specific mathematical concept, algorithm, or programming principle that distinguishes it from previously generated tasks.
    8. The 'Function Signature' should strictly follow the format: 'def function_name(parameters) -> return_type:', but the 'Solve' section must remain empty. Ensure that the input description corresponds to the expected parameters in the signature.
    
Ensure that the solution must not be any of the following titles:
- String Transformation with Vowel Count
- Custom Weighted Sorting
- Palindrome Substring Manipulation
- Nested Substring Compression
- Cyclic String Rotation and Character Frequency
- Nested List Product Calculation
- Selective Nested Function Evaluation
- Maximum Non-Adjacent Sum
- Graph Water Distribution Planning
- Consonant Cluster Reversal
- Shortest Path in a Weighted Grid
- Palindrome Compression
- Multi-Dimensional Array Spiral Sort
- String Pattern Replacer
- Matrix Diagonal Sum with Nested Conditions
- String Interleaving with Character Frequency
- Balanced Parentheses Scoring
- Character Sequence Extraction and Reversal
- Optimal Coin Change with Limited Supply
- Optimal Subarray Partition
- Nested Dictionary Path Evaluation
- Digit Frequency Sort with Multiples
- Custom Recursive Merge Sort with Conditional Swapping
- Dynamic Subset Sum with Constraints
- Graph Path with Prime Labeling
- Nested Fibonacci Sequence Evaluation
- Hierarchical Data Aggregation
- Multi-Dimensional Array Median Calculation
- Cycle Detection in Directed Graph with Constraints
- Minimum Cost Path with Obstacles
- String Segment Reversal with Unique Character Count
- Game Score Maximization with Constraints
- Isomorphic Graph Detection
- Advanced Alphanumeric Pattern Extraction
- Constrained Pyramid Formation
- Maximal Rectangle Area in Grid
- Priority Queue Simulation with Custom Criteria
- Weighted Nested List Sum
- Depth-first Search with Prime Node Values
- String Compression with Unique Character Count
- Hierarchical Employee Salary Adjustment
- Custom Radix Sort with Base Conversion
- Nested Array Element Swapper
- Graph Connectivity with Unique Path Count
- Optimal Subsequence Product with Constraints
- Graph Traversal with Unique Node Values
- Matrix Anti-Diagonal Sorting
- Custom Merge Sort with Inversion Count
- Graph Shortest Path with Conditional Detours
- Dynamic Subsequence Sum with Constraints
- Custom Radix Sort with Mixed Base Conversion
- Longest Increasing Subsequence with Unique Sum Constraint
- Optimal Path in Energy Efficiency Grid
- Custom Recursive Quick Sort with Median Pivot