Someone asked me this question:
You are given a list of intervals. You have to design an algorithm to find the sequence of non-overlapping intervals so that the sum of the range of intervals is maximum.
For Example:
If given intervals are:
["06:00","08:30"],
["09:00","11:00"],
["08:00","09:00"],
["09:00","11:30"],
["10:30","14:00"],
["12:00","14:00"]
Range is maximized when three intervals
[“06:00”, “08:30”],
[“09:00”, “11:30”],
[“12:00”, “14:00”],
are chosen.
Therefore, the answer is 420 (minutes).
This is a standard interval scheduling problem.
It can be solved by using dynamic programming.
Algorithm
Let there be n
intervals. sum[i]
stores maximum sum of interval up to interval i
in sorted interval array. The algorithm is as follows
Sort the intervals in order of their end timings.
sum[0] = 0
For interval i from 1 to n in sorted array
j = interval in 1 to i-1 whose endtime is less than beginning time of interval i.
If j exist, then sum[i] = max(sum[j]+duration[i],sum[i-1])
else sum[i] = max(duration[i],sum[i-1])
The iteration goes for n
steps and in each step, j
can be found using binary search, i.e. in log n
time.
Hence algorithm takes O(n log n)
time.
public int longestNonOverLappingTI(TimeInterval[] tis){
Arrays.sort(tis);
int[] mt = new int[tis.length];
mt[0] = tis[0].getTime();
for(int j=1;j<tis.length;j++){
for(int i=0;i<j;i++){
int x = tis[j].overlaps(tis[i])?tis[j].getTime():mt[i] + tis[j].getTime();
mt[j] = Math.max(x,mt[j]);
}
}
return getMax(mt);
}
public class TimeInterval implements Comparable <TimeInterval> {
public int start;
public int end;
public TimeInterval(int start,int end){
this.start = start;
this.end = end;
}
public boolean overlaps(TimeInterval that){
return !(that.end < this.start || this.end < that.start);
}
public int getTime(){
return end - start;
}
@Override
public int compareTo(TimeInterval timeInterval) {
if(this.end < timeInterval.end)
return -1;
else if( this.end > timeInterval.end)
return 1;
else{
//end timeIntervals are same
if(this.start < timeInterval.start)
return -1;
else if(this.start > timeInterval.start)
return 1;
else
return 0;
}
}
}
Heres the working code. Basically this runs in O(n^2) because of the two for loops. But as Shashwat said there are ways to make it run in O(n lg n)