def activity_selection(intervals): intervals.sort(key=lambda x: x[1]) # Sort by end time selected = [] last_end = 0 for start, end in intervals: if start >= last_end: selected.append((start, end)) last_end = end return selected Objective : Maximize value by stealing fractions of items (unlike 0/1 knapsack). Greedy Strategy : Prioritize items with the highest value/weight ratio.
(Disclaimer: This write-up focuses on general greedy algorithms. For specific Duohack platform problems, ensure you adhere to their licensing and usage policies.) duohack com greed exclusive
def fractional_knapsack(items, capacity): items.sort(key=lambda x: x.value / x.weight, reverse=True) total_value = 0 remaining = capacity for weight, value in items: if remaining <= 0: break take = min(remaining, weight) total_value += take * value / weight remaining -= take return total_value Objective : Build an optimal prefix-free binary code for data compression. Greedy Strategy : Use a priority queue to merge the two smallest nodes iteratively. def activity_selection(intervals): intervals
import heapq