feat(arrays): optimal task assignment

algorithms/arrays/optimal_task_assignment/README.md

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+# Optimal Task Assignment
+
+Assign tasks to workers so that the time it takes to complete all the tasks is minimized given a count of workers and an
+array where each element indicates the duration of a task.
+
+We wish to determine the optimal way in which to assign tasks to some workers. Each worker must work on exactly two
+tasks. Tasks are independent of each other, and each task takes a certain amount of time.

algorithms/arrays/optimal_task_assignment/__init__.py

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+from typing import List, Tuple
+
+
+def optimal_task_assignment(tasks: List[int]) -> List[Tuple[int, int]]:
+    """
+    After sorting the array, the for loop iterates for half the length of the array adds the pairs using indexing to a
+    list. So ~x is the bitwise complement operator which puts a negative sign in front of x and subtracts 1 from it.
+    Thus, the negative numbers as indexes mean that you count from the right of the array instead of the left. So,
+    numbers[-1] refers to the last element, numbers[-2] is the second-last, and so on. In this way, we are able to pair
+    the numbers from the beginning of the array to the end of the array.
+    """
+    sorted_tasks = sorted(tasks)
+    result: List[Tuple[int, int]] = []
+
+    for x in range(len(sorted_tasks) // 2):
+        result.append((sorted_tasks[x], sorted_tasks[~x]))
+
+    return result

algorithms/arrays/optimal_task_assignment/test_optimal_task_assignment.py

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+import unittest
+from . import optimal_task_assignment
+
+
+class OptimalTaskAssignmentTestCase(unittest.TestCase):
+    def test_1(self):
+        """Should return [(2,7), (3,6),(5,5)] from [6, 3, 2, 7, 5, 5]"""
+        tasks = [6, 3, 2, 7, 5, 5]
+        expected = [(2, 7), (3, 6), (5, 5)]
+        actual = optimal_task_assignment(tasks)
+        self.assertEqual(expected, actual)
+
+
+if __name__ == '__main__':
+    unittest.main()