Erase Overlapping Intervals Algorithm in C++ and Dart

Erase Overlapping Intervals Algorithm in C++ and Dart

This code implements a solution for the 'Erase Overlapping Intervals' problem, a classic example of interval scheduling, using a greedy approach. The goal is to find the minimum number of intervals to remove so that no overlaps remain in the given set of intervals.

C++ Implementation

class Solution {
public:
    static bool cmp(const vector<int>& a, const vector<int>& b) {
        return a[0] < b[0];
    }
    int eraseOverlapIntervals(vector<vector<int>>& intervals) {
        int result = 1;
        sort(intervals.begin(),intervals.end(),cmp);
        for(int i = 1; i < intervals.size(); i++) {
            if(intervals[i][0] >= intervals[i-1][1]) 
                result++;
            else 
                intervals[i][1] = min(intervals[i][1],intervals[i-1][1]);
        }
        return intervals.size() - result;
    }
};

Dart Implementation

class Solution {
    bool cmp(List<int> a, List<int> b) {
        return a[0] < b[0];
    }

    int eraseOverlapIntervals(List<List<int>> intervals) {
        int result = 1;
        intervals.sort(cmp);
        for(int i = 1; i < intervals.length; i++) {
            if(intervals[i][0] >= intervals[i-1][1]) 
                result++;
            else 
                intervals[i][1] = min(intervals[i][1],intervals[i-1][1]);
        }
        return intervals.length - result;
    }
}

Explanation:

1. Sorting: The intervals are sorted by their start times to ensure a greedy selection strategy. The cmp function handles the sorting comparison in both languages.
2. Iteration: The code iterates through the sorted intervals, comparing each interval's start time with the previous interval's end time.
3. Overlapping Check: If the current interval's start time is greater than or equal to the previous interval's end time, they don't overlap, and the result is incremented to count this non-overlapping interval. Otherwise, the current interval's end time is minimized to avoid further overlaps.
4. Result Calculation: Finally, the number of intervals to remove is calculated by subtracting the result (number of non-overlapping intervals) from the total number of intervals.

Key Points:

• This algorithm provides an efficient and optimal solution to the 'Erase Overlapping Intervals' problem.
• The greedy approach focuses on selecting intervals that maximize the number of non-overlapping intervals, leading to the minimum number of removals.
• The code is presented in both C++ and Dart, demonstrating the algorithm's adaptability across languages.