Lecture 34 CSE 331 Nov 20, 2017.

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Presentation transcript:

Lecture 34 CSE 331 Nov 20, 2017

CS Ed week (Dec 8) We’ll need volunteers! We need demos!

When to use Dynamic Programming There are polynomially many sub-problems OPT(1), …, OPT(n) Richard Bellman Optimal solution can be computed from solutions to sub-problems OPT(j) = max { vj + OPT( p(j) ), OPT(j-1) } There is an ordering among sub-problem that allows for iterative solution OPT (j) only depends on OPT(j-1), …, OPT(1)

Scheduling to min idle cycles n jobs, ith job takes wi cycles You have W cycles on the cloud What is the maximum number of jobs you can schedule?

Today’s agenda Dynamic Program for Subset Sum problem

May the Bellman force be with you