Lecture 37 CSE 331 Nov 4, 2009. Homework stuff (Last!) HW 10 at the end of the lecture Solutions to HW 9 on Monday Graded HW 9 on.

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Lecture 37 CSE 331 Nov 4, 2009

Homework stuff (Last!) HW 10 at the end of the lecture Solutions to HW 9 on Monday Graded HW 9 on Wednesday

Weighted Interval Scheduling Input: n jobs (s i,t i,v i ) Output: A schedule S s.t. no two jobs in S have a conflict Goal: max Σ j in S v j Assume: jobs are sorted by their finish time

Property of OPT OPT(j) = max { v j + OPT( p(j) ), OPT(j-1) }

A recursive algorithm M-Compute-Opt(j) If j = 0 then return 0 M[j] = max { v j + M-Compute-Opt( p(j) ), M-Compute-Opt( j-1 ) } If M[j] is not null then return M[j] return M[j] M-Compute-Opt(j) = OPT(j) Run time = O(# recursive calls)

Bounding # recursions M-Compute-Opt(j) If j = 0 then return 0 M[j] = max { v j + M-Compute-Opt( p(j) ), M-Compute-Opt( j-1 ) } If M[j] is not null then return M[j] return M[j] Whenever a recursive call is made an M value of assigned At most n values of M can be assigned O(n) overall

Recursion+ memory = Iteration Iteratively compute the OPT(j) values M[0] = 0 M[j] = max { v j + M[p(j)], M[j-1] } For j=1,…,n Iterative-Compute-Opt M[j] = OPT(j) O(n) run time

Reading Assignment Sec 6.1, 6.2 of [KT]