Description
(1) (10 points) Suppose n (≥ 1) people are stranded on a freeway due to a particularly heavy snowstorm.
Let us model the freeway as the real line. The locations of the stranded people are given by real numbers.
An emergency rescue operation found n hotels to potentially accommodate the n people. Assume that
each hotel has the capacity to shelter 1 person. However, due the prevailing road conditions access to
these hotels are severely limited. For each hotel H, there is a specific segment of the freeway such that
only people stranded in this segment can make it to H. Given as input the locations of the stranded
people, and a set of n segments of the freeway (each segement corresponding to a particular hotel), your
task is to design an efficient algorithm to decide if it is possible for all n people to find accommodation
for the night. (Assume that the input contains real numbers of finite precision, so that any arithmetic
operation on two real numbers takes constant time. Neither the list of people’s locations nor the list of
segments are assumed to be sorted in any particular order.)
(2) (15 points) Consider the following simplified model of how a law enforcement organization such as
the FBI apprehends the members of an organized crime ring. The crime ring has n members, denoted
by x1, . . . , xn. A law enforcement plan is a sequence of n actions, each of which is either:
• apprehending a member xj directly: this succeeds with probability qj ; or
• apprehending a member xj using another member, xi
, as a decoy: this action can only be taken
if xi was already apprehended in a previous step. The probability of success is pij .
Let’s assume that, if an attempt to apprehend xj fails, then xj will go into hiding in a country that
doesn’t allow extradition, and hence xj can never be apprehended after a failed attempt. Therefore, a
law enforcement plan is only considered valid if for each of the crime ring’s n members, the plan contains
only one attempt to apprehend him or her.
Assume we are given an input that specifies the number of members in the crime ring, n, and the
probabilities qj and pij for each i 6= j. You can assume these numbers are strictly positive and that
pij = pji for all i 6= j.
(2a) (5 points) Design an algorithm to compute a valid law enforcement plan that maximizes the
probability of apprehending all of the crime ring’s members, in the order x1, x2, . . . , xn. In other words,
for this part of the problem you should assume that the j
th action in the sequence should be an attempt
to apprehend xj , and the only thing your algorithm needs to decide is whether to apprehend xj directly
or to use one of the earlier members as a decoy, and if so, which decoy to use.
(2b) (10 points) Design an algorithm to compute a valid law enforcement plan that maximizes the
probability of apprehending all of the crime ring’s members, in any order. In other words, for this
part of the question, your algorithm must decide on the order in which to apprehend the crime ring’s
members and the sequence of operations to use to apprehend them in that order.
(3) (10 points) In this problem you are asked to implement Kruskal’s Minimum Spanning Tree Algorithm
and Prim’s Minimum Spanning Tree Algorithm. Your implementation should run in O(M log N) time,
as explained on page 150 and page 157 of the textbook. Implement the algorithm in Java. The only
libraries you are allowed to import are the ones in java.util.*. There is no Framework.java provided
for this assignment. You will need to implement your Java program from scratch.
Warning: Be aware that the running time of calling a method of a built-in Java class is
usually not constant-time, and take this into account when you think about the overall
running time of your code. For instance, if you use a LinkedList, and use the indexOf
method, this will take time linear in the number of elements in the list.
Your Java program should take in input from stdin and write output to stdout. You can use the Java
class Scanner to read input from System.in and use System.out.println to write to stdout. An
autograder will be online (the URL will be released on Piazza shortly) and come with options to
upload and test your code on a small number of public test cases. When we grade the assignment, we
will run it on a larger number of more complex test cases.
Your code should run in O(M log N) time. In particular, we impose a runtime limit of 2 seconds on
all runs, so that an asymptotically slower algorithm will likely not be able to complete the larger test
cases within the time limit. (In that situation, you will receive partial credit for the test cases that your
implementation computes in time.)
Your algorithm is to read data, representing a graph with edge costs, from the standard input in the
following format.
• The first line contains three integers separated by spaces, NMP, where 1 ≤ N ≤ 5000 is the
number of nodes, 1 ≤ M ≤ 25000000 is the number of edges, and P ∈ {0, 1}. If P = 0, Kruskal’s
Algorithm should be used. If P = 1, Prim’s Algorithm should be used.
• Each of the following M lines contains three integers XY C, where 1 ≤ X < Y ≤ N are two node
IDs in increasing order, and 0 ≤ C ≤ 2
31/M is a cost. Every such line denotes the presence of an
undirected edge between nodes X and Y of cost C.
Your algorithm should output data in the following format:
• N − 1 lines, containing one number E, where 1 ≤ E ≤ M. Each line should encode one edge
contained in the minimum spanning tree computed by your algorithm. Moreover, if P = 0, then
the edges should appear in the order they are added to the spanning tree by Kruskal’s Algorithm,
so the first line contains the first edge added (i.e. the cheapest edge in the graph); if P = 1, then
the edges should appear in the order they are added by Prim’s Algorithm. (Ties should be broken
by adding lower-numbered edges first.)
Example:
• Input:
3 3 0 # 3 nodes, 3 edges, use Kruskal’s
1 2 100 # edge 1: cost({1, 2}) = 100
2 3 200 # edge 2: cost({2, 3}) = 200
1 3 150 # edge 3: cost({1, 3}) = 150
• Expected Output:
1 # Kruskal’s first selects edge 1
3 # Kruskal’s then selects edge 3, completing the MST
We will impose a runtime limit of 2 seconds on each instance. In particular, this means that for a
maximally-sized instance (with M = 25000000), on a 2GHz machine, you only have 160 clock cycles
per edge – an algorithm with complexity O(MN) would not finish in time even if the constant hidden
by big-O notation is 1. (We may slightly adjust this number or size of test cases if Java turns out to be
too slow on the testing rig.)
We will use Java 8 for compiling and testing your program. More details on the build and testing
environment will be made available on the autograder website once it comes online.
Remember: The problem asks you to implement both the Kruskal’s and the Prim’s MST algorithms.
Use class Scanner to read input from stdin and use System.out.println to output to stdout. You
may find the class PriorityQueue useful.
