# Difference between revisions of "Chapter 1"

Problems

1.1. Show that a + b can be less than min(a, b).

1.2. Show that a × b can be less than min(a, b).

1.3. Design/draw a road network with two points a and b such that the fastest route between a and b is not the shortest route.

1.4. Design/draw a road network with two points a and b such that the shortest route between a and b is not the route with the fewest turns.

1.5. The knapsack problem is as follows: given a set of integers S = {s1, s2. . . , sn}, and a target number T, find a subset of S that adds up exactly to T. For example, there exists a subset within S = {1, 2, 5, 9, 10} that adds up to T = 22 but not T = 23.
Find counterexamples to each of the following algorithms for the knapsack problem. That is, give an S and T where the algorithm does not find a solution that leaves the knapsack completely full, even though a full-knapsack solution exists.
(a) Put the elements of S in the knapsack in left to right order if they fit, that is, the first-fit algorithm.
(b) Put the elements of S in the knapsack from smallest to largest, that is, the best-fit algorithm.
(c) Put the elements of S in the knapsack from largest to smallest.

1.6. The set cover problem is as follows: given a set S of subsets S1, . . . , Sm of the universal set U = {1, ..., n}, find the smallest subset of subsets T ⊆ S such that ∪ti∈T ti = U. For example, consider the subsets S1 = {1, 3, 5}, S2 = {2, 4}, S3 = {1, 4}, and S4 = {2, 5}. The set cover of {1, . . . , 5} would then be S1 and S2.
Find a counterexample for the following algorithm: Select the largest subset for the cover, and then delete all its elements from the universal set. Repeat by adding the subset containing the largest number of uncovered elements until all are covered.

1.7. The maximum clique problem in a graph G = (V, E) asks for the largest subset C of vertices V such that there is an edge in E between every pair of vertices in C. Find a counterexample for the following algorithm: Sort the vertices of G from highest to lowest degree. Considering the vertices in order of degree, for each vertex add it to the clique if it is a neighbor of all vertices currently in the clique. Repeat until all vertices have been considered.
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