**ishiney @ Sun May 12, 2013 3:43 pm wrote:**

DP O(N^2) solution for #2:

First, assume that the given child is the "bottom" child (that is, it inherited at least the first & last genes from the 2nd parent). Trivially, check if the minimum # of mutations decreases by assuming it as the "top" child.

Let dp[start][length] be our states (length being the distance between the 2 indices/crossover endpoints, start being the index of the leftmost endpoint). Initialize dp[i][0] for all relevant i to the differences between the bottom child and bottom parent. Transform between dp[i][j] --> dp[i][j+1] by using the precomputed value for dp[i][j], then noting whether there's an increase/decrease/no change in # of mutation after including j+1 in the crossover. Take minimum over all valid ranges for answer.

O(N^2) states, O(1) transition time, thus O(N^2) solution.

That sounds good, thanks for posting! You can also do it without the O(n^2) space requirement of the dp array by pre-computing a "base mutation rate" between the child and each parent, and then updating those mutation rates one bit at a time as you search through the various crossover points, keeping track of the smallest value so far as you go.

Sam.