From 2364494193359c16160ee760bd02da995ab314d7 Mon Sep 17 00:00:00 2001 From: Hardik Pawar Date: Wed, 2 Oct 2024 12:41:04 +0530 Subject: [PATCH] Add activity selection new algorithm --- greedy_methods/activity_selection.py | 52 ++++++++++++++++++++++++++++ 1 file changed, 52 insertions(+) create mode 100644 greedy_methods/activity_selection.py diff --git a/greedy_methods/activity_selection.py b/greedy_methods/activity_selection.py new file mode 100644 index 000000000..ab5405ddb --- /dev/null +++ b/greedy_methods/activity_selection.py @@ -0,0 +1,52 @@ +""" +The Activity Selection Problem is a classic problem in which a set of activities, +each with a start and end time, needs to be scheduled in such a way that +the maximum number of non-overlapping activities is selected. +This is a greedy algorithm where at each step, +we choose the activity that finishes the earliest +and does not conflict with previously selected activities. + +Wikipedia: https://en.wikipedia.org/wiki/Activity_selection_problem +""" + + +def activity_selection(activities: list[tuple[int, int]]) -> list[tuple[int, int]]: + """ + Solve the Activity Selection Problem using a greedy algorithm by selecting + the maximum number of non-overlapping activities from a list of activities. + + Parameters: + activities: A list of tuples where each tuple contains + the start and end times of an activity. + + Returns: + A list of selected activities that are non-overlapping. + + Example: + >>> activity_selection([(1, 3), (2, 5), (3, 9), (6, 8)]) + [(1, 3), (6, 8)] + + >>> activity_selection([(0, 6), (1, 4), (3, 5), (5, 7), (5, 9), (8, 9)]) + [(1, 4), (5, 7), (8, 9)] + + >>> activity_selection([(1, 2), (2, 4), (3, 5), (0, 6)]) + [(1, 2), (2, 4)] + + >>> activity_selection([(5, 9), (1, 2), (3, 4), (0, 6)]) + [(1, 2), (3, 4), (5, 9)] + """ + + # Step 1: Sort the activities by their end time + sorted_activities = sorted(activities, key=lambda x: x[1]) + + # Step 2: Select the first activity (the one that finishes the earliest) + # as the initial activity + selected_activities = [sorted_activities[0]] + + # Step 3: Iterate through the sorted activities and select the ones + # that do not overlap with the last selected activity + for i in range(1, len(sorted_activities)): + if sorted_activities[i][0] >= selected_activities[-1][1]: + selected_activities.append(sorted_activities[i]) + + return selected_activities