def apply_operations_to_maximize_score_brute_force(numbers, operations):
    max_score = 0
    number_of_operations = len(operations)

    # Iterate through all possible combinations of operations
    for i in range(2 ** number_of_operations):
        current_numbers = numbers[:]
        current_score = 0

        # Apply operations based on the current combination
        for operation_index in range(number_of_operations):

            # Check if the current operation is included in the combination
            if (i >> operation_index) & 1:

                # Apply the operation to the current numbers
                index = operations[operation_index][0]
                value = operations[operation_index][1]
                current_numbers[index] += value

        # Calculate the score for the current combination
        for number in current_numbers:
            current_score += number

        # Update the maximum score if necessary
        max_score = max(max_score, current_score)

    return max_score

def apply_operations_to_maximize_score(numbers, operations):
    max_score = float('-inf')

    def calculate_score(current_numbers):
        score = 0
        for number in current_numbers:
            score += number
        return score

    def find_max_score(index, current_numbers):
        nonlocal max_score

        # Base case: all operations have been considered
        if index == len(operations):
            current_score = calculate_score(current_numbers)
            max_score = max(max_score, current_score)
            return

        # Option 1: Don't apply the current operation
        find_max_score(index + 1, current_numbers[:])

        # Option 2: Apply the current operation

        operation_index = operations[index][0]
        operation_value = operations[index][1]

        # Create a copy of current_numbers to avoid modifying the original
        new_numbers = current_numbers[:]
        new_numbers[operation_index] += operation_value

        find_max_score(index + 1, new_numbers)

    # Begin the recursive search.
    find_max_score(0, numbers[:])

    # Return the maximum score found.
    return max_score

def apply_operations_to_maximize_score(numbers, prime_factors, operation_count):
    prime_numbers_available = sorted(prime_factors, reverse=True)
    current_score = 1
    operations_applied = 0

    # Processing primes in descending order to maximize score.
    for prime_number in prime_numbers_available:

        # Early exit if we've used all our operations.
        if operations_applied >= operation_count:
            break

        current_score *= prime_number
        operations_applied += 1

    numbers_length = len(numbers)
    remaining_operations = operation_count - operations_applied

    # Use remaining operations with numbers array.
    for i in range(min(remaining_operations, numbers_length)):
        current_score *= numbers[i]

    return current_score