Difference between pages "Chapter 11" and "3.27"

From The Algorithm Design Manual Solution Wiki
(Difference between pages)
Jump to navigation Jump to search
 
(Created page with "Let's put into the black box whole set <math>S=\{x_i\}_{i=1}^n</math>. If <math>bb(S)</math> is True, then such a subset exists and we can go on: # R:=S # for i:=1 to n do ##...")
 
Line 1: Line 1:
=NP-Completeness=
+
Let's put into the black box whole set <math>S=\{x_i\}_{i=1}^n</math>. If <math>bb(S)</math> is True, then such a subset exists and we can go on:
 +
# R:=S
 +
# for i:=1 to n do
 +
## If <math>bb(R/\{x_i\})</math> is True then <math>R:=R/\{x_i\}</math>
 +
When this iteration is finished R will be subset of S that adds up to k.
  
===Transformations and Satisfiability===
+
Above solution works even when there are multiple subsets that add up to k.
  
:[[11.1]]. Give the 3-SAT formula that results from applying the reduction of SAT to 3-SAT for the formula:
 
:::<math> (x\or y \or \overline z \or w \or u \or \overline v) \and (\overline x \or \overline
 
y \or z \or \overline w \or u \or v) \and (x \or \overline y \or \overline z \or w \or u \or \overline v)\and (x \or \overline y) </math>
 
[[11.1|Solution]]
 
  
 
+
Back to [[Chapter 3]]
:11.2. Draw the graph that results from the reduction of 3-SAT to vertex cover for the expression
 
:::<math>(x \or \overline y \or z) \and (\overline x \or y \or \overline z) \and(\overline x \or y \or z) \and (x \or \overline y \or \overline x) </math>
 
 
 
 
 
:[[11.3]]. Prove that 4-SAT is NP-hard.
 
[[11.3|Solution]]
 
 
 
 
 
:11.4. ''Stingy'' SAT is the following problem: given a set of clauses (each a disjunction of literals) and an integer <math>k</math>, find a satisfying assignment in which at most <math>k</math> variables are true, if such an assignment exists. Prove that stingy SAT is NP-hard.
 
 
 
 
 
:[[11.5]]. The ''Double SAT'' problem asks whether a given satisfiability problem has '''at least two different satisfying assignments'''. For example, the problem <math>{{v1, v2}, {v_1, v_2}, {v_1, v_2}}</math> is satisfiable, but has only one solution <math>(v_1 =F, v_2 = T)</math>. In contrast, <math>{{v_1, v_2}, {v_1, v_2}}</math> has exactly two solutions. Show that Double-SAT is NP-hard.
 
[[11.5|Solution]]
 
 
 
 
 
:11.6. Suppose we are given a subroutine that can solve the traveling salesman decision problem on page 357 in (say) linear time. Give an efficient algorithm to find the actual TSP tour by making a polynomial number of calls to this subroutine.
 
 
 
 
 
:[[11.7]]. Implement a SAT to 3-SAT reduction that translates satisfiability instances into equivalent 3-SAT instances.
 
[[11.7|Solution]]
 
 
 
 
 
:11.8. Design and implement a backtracking algorithm to test whether a set of clause sets is satisfiable. What criteria can you use to prune this search?
 
 
 
 
 
:[[11.9]]. Implement the vertex cover to satisfiability reduction, and run the resulting clauses through a satisfiability solver code. Does this seem like a practical way to compute things?
 
[[11.9|Solution]]
 
 
 
===Basic Reductions===
 
 
 
:11.10. An instance of the ''set cover'' problem consists of a set <math>X</math> of <math>n</math> elements, a family <math>F</math> of subsets of <math>X</math>, and an integer <math>k</math>. The question is, does there exist <math>k</math> subsets from <math>F</math> whose union is <math>X</math>? For example, if <math>X = \{1,2,3,4\}</math> and <math>F = \{ \{1,2\}, \{2,3\}, \{4\}, \{2,4\} \}</math>, there does not exist a solution for <math>k=2</math>, but there does for <math>k=3</math> (for example, <math> \{1,2\}, \{2,3\}, \{4\}</math>). Prove that set cover is NP-complete with a reduction from vertex cover.
 
 
 
 
 
:[[11.11]]. The ''baseball card collector problem'' is as follows. Given packets <math>P_1, \ldots, P_m</math>, each of which contains a subset of this year's baseball cards, is it possible to collect all the year's cards by buying <math>\leq k</math> packets? For example, if the players are <math> \{Aaron, Mays, Ruth, Steven \} </math> and the packets are
 
:::<math> \{ \{Aaron,Mays\}, \{Mays,Ruth\}, \{Steven\}, \{Mays,Steven\} \}, </math>
 
:there does not exist a solution for <math>k=2</math>, but there does for <math>k=3</math>, such as
 
:::<math> \{Aaron,Mays\}, \{Mays,Ruth\}, \{Steven\} </math>
 
:Prove that the baseball card collector problem is NP hard using a reduction from vertex cover.
 
 
 
 
 
:11.12. The ''low-degree spanning tree problem'' is as follows. Given a graph <math>G</math> and an integer <math>k</math>, does <math>G</math> contain a spanning tree such that all vertices in the tree have degree ''at most'' <math>k</math> (obviously, only tree edges count towards the degree)? For example, in the following graph, there is no spanning tree such that all vertices have a degree less than three.
 
\fixedfigsize{pictures/lowdegree.png}{1.0in}
 
#Prove that the low-degree spanning tree problem is NP-hard with a reduction from Hamiltonian ''path''.
 
#Now consider the ''high-degree spanning tree problem'', which is as follows. Given a graph <math>G</math> and an integer <math>k</math>, does <math>G</math> contain a spanning tree whose highest degree vertex is ''at least'' <math>k</math>? In the previous example, there exists a spanning tree with a highest degree of 8. Give an efficient algorithm to solve the high-degree spanning tree problem, and an analysis of its time complexity.
 
 
 
 
 
:[[11.13]].In the minimum element set cover problem, we seek a set cover <math>S \subseteq C</math> of a universal set <math>U = {1, . . . , n}</math> such that sum of the sizes of the subsets in <math>S</math> is at most <math>k</math>.
 
::(a) Show that <math>C = {{1, 2, 3}, {1, 3, 4}, {2, 3, 4}, {3, 4, 5}}</math> has a cover of size 6, but none of size 5 because of a repeated element.
 
::(b) Prove that this problem is NP-hard. (Hint: set cover remains hard if all subsets are of the same size.)
 
[[11.13|Solution]]
 
 
 
 
 
:11.14. The ''half-Hamiltonian cycle problem'' is, given a graph <math>G</math> with <math>n</math> vertices, determine whether <math>G</math> has a simple cycle of length exactly <math>[n/2]</math>, where the floor function rounds its input down to the nearest integer. Prove that this problem is NP-hard.
 
 
 
 
 
:[[11.15]]. The 3-phase power balance problem asks for a way to partition a set of n positive integers into three sets <math>A</math>, <math>B</math>, or <math>C</math> such that <math>\sum_{i} a_i = \sum_{i} b_i = \sum_{i} c_i</math>. Prove that this problem is NP-hard using a reduction from integer partition or subset sum (see Section 10.5 (page 329)).
 
[[11.15|Solution]]
 
 
 
 
 
:11.16. Show that the following problem is NP-complete:
 
:* ''Problem:'' Dense subgraph
 
:* ''Input:'' A graph <math>G</math>, and integers <math>k</math> and <math>y</math>.
 
:* ''Output:'' Does <math>G</math> contain a subgraph with exactly <math>k</math> vertices and at least <math>y</math> edges?
 
 
 
 
 
:[[11.17]]. Show that the following problem is NP-complete:
 
:* ''Problem:'' Clique, no-clique
 
:* ''Input:'' An undirected graph <math>G=(V,E)</math> and an integer <math>k</math>.
 
:* ''Output:'' Does <math>G</math> contain both a clique of size <math>k</math> and an independent set of size <math>k</math>.
 
[[11.17|Solution]]
 
 
 
 
 
:11.18. n ''Eulerian cycle'' is a tour that visits every edge in a graph exactly once. An ''Eulerian subgraph'' is a subset of the edges and vertices of a graph that has an Eulerian cycle. Prove that the problem of finding the number of edges in the largest Eulerian subgraph of a graph is NP-hard. (Hint: the Hamiltonian circuit problem is NP-hard even if each vertex in the graph is incident upon exactly three edges.)
 
 
 
 
 
:[[11.19]]. Show that the following problem is NP-hard:
 
:*''Problem:'' Maximum Common Subgraph
 
:*''Input:'' Two graphs <math>G_1 = (V_1, E_1)</math> and <math>G_2 = (V_2, E_2)</math>, and a budget <math>b</math>.
 
:*Output: Two sets of nodes <math>S_1 \subseteq V_1</math> and <math>S_2 \subseteq V_2</math> whose deletion leaves at least <math>b</math> nodes in each graph, and makes the two graphs identical.
 
[[11.19|Solution]]
 
 
 
 
 
:11.20. A ''strongly independent'' set is a subset of vertices <math>S</math> in a graph <math>G</math> such that for any two vertices in <math>S</math>, there is no path of length two in <math>G</math>. Prove that strongly independent set is NP-hard.
 
 
 
 
 
:[[11.21]]. A ''kite'' is a graph on an even number of vertices, say <math>2n</math>, in which <math>n</math> of the vertices form a clique and the remaining <math>n</math> vertices are connected in a tail that consists of a path joined to one of the vertices of the clique. Given a graph and a goal g, the ''max kite'' problem asks for a subgraph that is a kite and contains <math>2g</math> nodes. Prove that ''max kite'' is NP-hard.
 
[[11.21|Solution]]
 
 
 
===Creative Reductions===
 
 
 
:11.22. Prove that the following problem is NP-complete:
 
:* ''Problem:'' Hitting Set
 
:* ''Input:'' A collection <math>C</math> of subsets of a set <math>S</math>, positive integer <math>k</math>.
 
:* ''Output:'' Does <math>S</math> contain a subset <math>S'</math> such that <math>|S'| \leq k</math> and each subset in <math>C</math> contains at least one element from <math>S'</math>?
 
 
 
 
 
:[[11.23]]. Prove that the following problem is NP-complete:
 
:* ''Problem:'' Knapsack
 
:* ''Input:'' A set <math>S</math> of <math>n</math> items, such that the <math>i</math>th item has value <math>v_i</math> and weight <math>w_i</math>.  Two positive integers: weight limit <math>W</math> and value requirement <math>V</math>.
 
:* ''Output:'' Does there exist a subset <math>S' \in S</math> such that <math>\sum_{i \in S'} w_i \leq W</math> and <math>\sum_{i \in S'} v_i \geq V</math>?
 
:(Hint: start from integer partition.)
 
[[11.23|Solution]]
 
 
 
 
 
:11.24. Prove that the following problem is NP-complete:
 
:* ''Problem:'' Hamiltonian Path
 
:* ''Input:'' A graph <math>G</math>, and vertices <math>s</math> and <math>t</math>.
 
:* ''Output:'' Does <math>G</math> contain a path which starts from <math>s</math>, ends at <math>t</math>, and visits all vertices without visiting any vertex more than once? (Hint: start from Hamiltonian cycle.)
 
 
 
 
 
:[[11.25]]. Prove that the following problem is NP-complete:
 
:* ''Problem:'' Longest Path
 
:* ''Input:'' A graph <math>G</math> and positive integer <math>k</math>.
 
:* ''Output:'' Does <math>G</math> contain a path that visits at least <math>k</math> different vertices without visiting any vertex more than once?
 
[[11.25|Solution]]
 
 
 
 
 
:11.26. Prove that the following problem is NP-complete:
 
:* ''Problem:'' Dominating Set
 
:* ''Input:'' A graph <math>G=(V,E)</math> and positive integer <math>k</math>.
 
:* ''Output:'' Is there a subset <math>V' \in V</math> such that <math>|V'|\leq k</math> where for each vertex <math>x \in V</math> either <math>x \in V'</math> or there exists an edge <math>(x,y)</math>, where <math>y \in V'</math>.
 
 
 
 
 
:[[11.27]]. Prove that the vertex cover problem (does there exist a subset <math>S</math> of <math>k</math> vertices in a graph <math>G</math> such that every edge in <math>G</math> is incident upon at least one vertex in <math>S</math>?) remains NP-complete even when all the vertices in the graph are restricted to have even degrees.
 
[[11.27|Solution]]
 
 
 
 
 
:11.28. Prove that the following problem is NP-complete:
 
:* ''Problem:'' Set Packing
 
:* ''Input:'' A collection <math>C</math> of subsets of a set <math>S</math>, positive integer <math>k</math>.
 
:* ''Output:'' Does <math>S</math> contain at least <math>k</math> disjoint subsets (i.e., such that none of these subsets have any elements in common?)
 
 
 
 
 
:[[11.29]]. Prove that the following problem is NP-complete:
 
:* ''Problem:'' Feedback Vertex Set
 
:* ''Input:'' A directed graph <math>G=(V,A)</math> and positive integer <math>k</math>.
 
:* ''Output:'' Is there a subset <math>V' \in V</math> such that <math>|V'|\leq k</math>, such that deleting the vertices of <math>V'</math> from <math>G</math> leaves a DAG?
 
[[11.29|Solution]]
 
 
 
 
 
:11.30. Give a reduction from Sudoku to the vertex coloring problem in graphs. Specifically, describe how to take any partially filled Sudoku board and construct a graph that can be colored with nine colors iff the Sudoku board is solvable.
 
 
 
===Algorithms for Special Cases===
 
 
 
:[[11.31]]
 
 
 
 
 
:11.32
 
 
 
 
 
:[[11.33]]
 
 
 
 
 
:11.34
 
 
 
 
 
:[[11.35]]
 
 
 
 
 
Back to [[Chapter List]]
 

Latest revision as of 18:06, 20 September 2020

Let's put into the black box whole set [math]\displaystyle{ S=\{x_i\}_{i=1}^n }[/math]. If [math]\displaystyle{ bb(S) }[/math] is True, then such a subset exists and we can go on:

  1. R:=S
  2. for i:=1 to n do
    1. If [math]\displaystyle{ bb(R/\{x_i\}) }[/math] is True then [math]\displaystyle{ R:=R/\{x_i\} }[/math]

When this iteration is finished R will be subset of S that adds up to k.

Above solution works even when there are multiple subsets that add up to k.


Back to Chapter 3