Task Scheduler

You are given an array of tasks where each task is represented as a pair of positive integers [duration, deadline]. The task's duration is the time it takes to complete the task, and the deadline is the time by which the task should ideally be completed. When scheduling tasks sequentially (i.e., one after another), the completion time for a task is the sum of the durations of all tasks scheduled before it plus its own duration.

A task incurs a penalty if its completion time exceeds its deadline. The penalty for a task is defined as:

penalty = max(0, completion_time - deadline)

Your goal is to determine an ordering of the tasks that minimizes the total penalty (i.e., the sum of the penalties of all tasks). If there are multiple orderings that yield the same minimum total penalty, you can return any one of them.

**Input:

• tasks: An array of tasks, where each task is represented as an array or tuple [duration, deadline].**

**Output:

• An array of indices representing the order in which to execute the tasks.**

Example:

Suppose you have the following tasks:

tasks = [
  [3, 4],  // Task 0: duration 3, deadline 4
  [2, 2],  // Task 1: duration 2, deadline 2
  [1, 3]   // Task 2: duration 1, deadline 3
]

One possible ordering might result in different total penalties. Your task is to implement a function (in the language of your choice) that computes an ordering of tasks (by outputting their indices) which minimizes the cumulative penalty.

Function Signature Example:

function scheduleTasks(tasks) {
  // Your code here
}

Constraints:

• 1 <= tasks.length <= 10^5
• 1 <= duration, deadline <= 10^9

Ensure that your solution is efficient and can handle large inputs.