Solved CSCI 570 HW 6 Note This homework assignment covers dynamic programming.

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CSCI 570 HW 6

Note This homework assignment covers dynamic programming. It is recommended that you read chapter 6.1 to 6.4 from Klienberg and Tardos.

1 Graded Problems

1. From the lecture, you know how to use dynamic programming to solve the
0-1 knapsack problem where each item is unique and only one of each kind
is available. Now let us consider knapsack problem where you have infinitely many items of each kind. Namely, there are n different types of
items. All the items of the same type i have equal size wi and value vi
.

You are offered with infinitely many items of each type. Design a dynamic
programming algorithm to compute the optimal value you can get from a
knapsack with capacity W.

2. Given a non-empty string s and a dictionary containing a list of unique
words, design a dynamic programming algorithm to determine if s can
be segmented into a space-separated sequence of one or more dictionary
words. If s=“algorithmdesign” and your dictionary contains “algorithm”
and “design”. Your algorithm should answer Yes as s can be segmented as
“algorithmdesign”.

3. Given n balloons, indexed from 0 to n − 1. Each balloon is painted with
a number on it represented by array nums. You are asked to burst all the
balloons. If the you burst balloon i you will get nums[lef t] ∗ nums[i] ∗
nums[right] coins. Here left and right are adjacent indices of i. After the burst, the left and right then becomes adjacent. You may assume
nums[−1] = nums[n] = 1 and they are not real therefore you can not
burst them. Design an dynamic programming algorithm to find the maximum coins you can collect by bursting the balloons wisely. Analyze the

running time of your algorithm.

Here is an example. If you have the nums arrays equals [3, 1, 5, 8]. The
optimal solution would be 167, where you burst balloons in the order of 1,
5 3 and 8.

The left balloons after each step is:
[3, 1, 5, 8] → [3, 5, 8] → [3, 8] → [8] → []
And the coins you get equals:
167 = 3 ∗ 1 ∗ 5 + 3 ∗ 5 ∗ 8 + 1 ∗ 3 ∗ 8 + 1 ∗ 8 ∗ 1.

4. Solve Kleinberg and Tardos, Chapter 6, Exercise 5.

2 Practice Problems
5. Solve Kleinberg and Tardos, Chapter 6, Exercise 6.
6. Solve Kleinberg and Tardos, Chapter 6, Exercise 10.
7. Solve Kleinberg and Tardos, Chapter 6, Exercise 24.