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In this approach, we prioritize seeds with shorter planting times first. The idea is that we can start planting these seeds earlier, and consequently, they will finish blooming earlier. This might minimize the delay caused by longer-growing seeds.
Time Complexity: O(n log n) due to sorting. Space Complexity: O(n) for storing seeds in an array.
1using System;
2using System.Linq;
3
4class Seed {
5 public int PlantTime { get; set; }
6 public int GrowTime { get; set; }
7}
8
9class Program {
10 public static int EarliestFullBloom(int[] plantTime, int[] growTime) {
11 Seed[] seeds = new Seed[plantTime.Length];
12
13 for (int i = 0; i < plantTime.Length; i++) {
14 seeds[i] = new Seed { PlantTime = plantTime[i], GrowTime = growTime[i] };
15 }
16
17 Array.Sort(seeds, (a, b) => a.PlantTime.CompareTo(b.PlantTime));
18
19 int currentDay = 0;
20 int lastBloomDay = 0;
21
22 foreach (var seed in seeds) {
23 currentDay += seed.PlantTime;
24 lastBloomDay = Math.Max(lastBloomDay, currentDay + seed.GrowTime);
25 }
26
27 return lastBloomDay;
28 }
29
30 static void Main() {
31 int[] plantTime = { 1, 4, 3 };
32 int[] growTime = { 2, 3, 1 };
33 Console.WriteLine("Earliest Full Bloom Day: " + EarliestFullBloom(plantTime, growTime));
34 }
35}
36This C# implementation uses a Seed class to manage data, sorts them based on plant times, and sequentially calculates the full bloom day.
This strategy focuses on seeds with longer grow times first. By doing so, we minimize delays caused by excessively long growing periods by ensuring they finish growing as soon as possible.
Time Complexity: O(n log n) because of sorting operations. Space Complexity: O(n) for storing seed data.
1
This solution focuses on sorting the seeds based on maximum grow time first.
This helps accommodate delays caused by these seeds. It updates the potential maximum bloom day accordingly.