OCR Further Discrete 2024 June — Question 5 18 marks

Exam BoardOCR
ModuleFurther Discrete (Further Discrete)
Year2024
SessionJune
Marks18
PaperDownload PDF ↗
Mark schemeDownload PDF ↗
TopicTravelling Salesman
TypeClassical vs Practical TSP
DifficultyModerate -0.3 This is a standard Further Maths Decision Maths question covering routine TSP algorithms (nearest neighbour, lower bounds via deletion). Parts (a)-(b) test basic conceptual understanding, while (c)-(h) involve straightforward application of well-rehearsed algorithms to a small network. The question requires multiple steps but no novel insight or problem-solving beyond textbook procedures.
Spec7.04b Minimum spanning tree: Prim's and Kruskal's algorithms7.04c Travelling salesman upper bound: nearest neighbour method7.04d Travelling salesman lower bound: using minimum spanning tree

5
  1. Write down a way in which the nearest neighbour method can fail to solve the problem of finding a least weight cycle through all the vertices of a network.
  2. Explain why, when trying to find a least weight cycle through all the vertices of a network, an ad hoc method may be preferable to an algorithmic approach. The distance matrix below represents a network connecting six viewpoints \(\mathrm { A } , \mathrm { B } , \mathrm { C } , \mathrm { D } , \mathrm { E }\) and F . The distance matrix shows the direct distances between each pair of viewpoints where a direct route exists.
    The distances are measured in km.
    A blank shows that there is no direct route between the two viewpoints.
    ABCDEF
    A64
    B6529
    C51576
    D42155
    E975
    F6
  3. Draw the network on the vertices given in the Printed Answer Booklet.
  4. Apply the nearest neighbour method, starting from A. A hiker wants to travel between the six viewpoints, starting and finishing at A.
    The hiker must visit every viewpoint at least once, but may visit a viewpoint more than once.
  5. Show that the hiker does not need to travel as far as 50 km .
  6. Use an appropriate algorithm to find the shortest distance from F to each of the other viewpoints.
  7. Complete the table in the Printed Answer Book to show the shortest distance between each pair of viewpoints.
  8. Use your answer to part (g) to find a lower bound for the distance the hiker must travel by initially deleting vertex A.

Question 5:
AnswerMarks Guidance
5(a) Nearest neighbour can stall
[1]2.5 e.g. may not find a cycle or may not find least weight cycle
BOD descriptions that do not close the cycle
Accept valid descriptions concerning the structure of the graph
but not descriptions using hypothetical weights
AnswerMarks Guidance
5(b) Ad hoc method is likely to find an acceptable
solution and is quicker than checking every
AnswerMarks Guidance
possible cycleB1
[1]2.4 Solution is good enough and method is quick
Accept ‘quicker’ or ‘easier’ or ‘more efficient’, o.e.
Or any of the following o.e.
Algorithmic approach is likely to involve an exhaustive check
Algorithmic approach finds (upper and lower) bounds only (not
necessarily optimal solution)
No known algorithm (currently) (for TSP)
AnswerMarks Guidance
5(c) B 5 C
2 15
6 9
A 4 D
6 7
5
AnswerMarks
F EM1
A1
AnswerMarks
[2]1.1
1.1Correct arcs (i.e graph correct)
At most one missing or extra arc
Ignore any working for part (f)
Correct network, i.e. correct graph weighted correctly, with no
errors. Allow ambiguous placing if plausibly correct
AnswerMarks Guidance
5(d) A – D – B – C – F
Stalls before visiting EM1
A1
AnswerMarks
[2]1.1
1.1A – D – B – C – F
No E or ‘stall’ or ‘stop’ or other explicit evidence that n.n. does not
reach every vertex
AnswerMarks Guidance
5(e) e.g. A – B – C – F – C – E – D – A
Length = 39(km)M1
A1
AnswerMarks
[2]3.4
3.4Any closed route through all six vertices, using only arcs from QP
Correct length of their route, provided it is less than 50 (km)
AnswerMarks Guidance
5(f) Dijkstra’s algorithm starting from F
A 6 17 B 3 11 C 2 6
17 11 6
D 4 13 E 5 13 F 1 0
21 13 13
F to B = 11 (km) and F to C = 6 (km)
AnswerMarks
F to A = 17, F to D = 13, F to E = 13 (km)M1*
A1
M1d*
A1
A1
AnswerMarks
[5]3.1a
1.1
1.1
1.1
AnswerMarks
1.1Evidence of using Dijkstra’s algorithm
May be seen on diagram from part (c)
Need not use box format
Order of labelling not necessary
Using F as the starting vertex
Evidence of updating (at D if starting from F but e.g. at C if starting
from A)
Shortest distance F to B = 11, F to C = 6
Correct in a list or table or seen as permanent labels, o.e.
Shortest distances F to A = 17, F to D = 13, F to E = 13
Correct in a list or table or seen as permanent labels, o.e.
SC
If M0 for dependent method mark (i.e. at best M1 A1 M0) then
SCB1 for all distances correct
F to A = 17, F to B = 11, F to C = 6, F to D = 13, F to E = 13
AnswerMarks Guidance
513
5(g) A B C D E F
A 6 11 4 9 17
B 6 5 2 7 11
C 11 5 7 7 6
D 4 2 7 5 13
E 9 7 7 5 13
AnswerMarks
F 17 11 6 13 13B1
B1
AnswerMarks
[2]2.1
3.1bIgnore errors or omissions in row F and column F
Lead diagonal may be blank or ‘0’ or ‘–‘ or similar,
but not contain any non-zero values
Bold values correct (unshaded values excluding row F and col F)
All shaded values correct
AnswerMarks Guidance
5(h) e.g.
BC = 5 B C
BD = 2
DE = 5 D
CF = 6
F E
AD = 4 and AB = 6
(lower bound) 18 + 10
AnswerMarks
= 28M1
M1
A1
AnswerMarks
[3]3.4
2.2a
AnswerMarks
2.2aAny spanning tree for {B, C, D, E, F} or {A, B, C, D, E, F}
(need not be MST)
Arcs may be listed (in any order) or tree shown as a diagram
Weights are not necessary here
Use two (different) least weight arcs from A,
for example see AB and AD (and no others) or see 4+6 or see +10
or implied from final answer 28
28 cao from correct MST for {B, C, D, E, F} or {A, B, C, D, E, F}
AnswerMarks Guidance
611 4
Question 5:
5 | (a) | Nearest neighbour can stall | B1
[1] | 2.5 | e.g. may not find a cycle or may not find least weight cycle
BOD descriptions that do not close the cycle
Accept valid descriptions concerning the structure of the graph
but not descriptions using hypothetical weights
5 | (b) | Ad hoc method is likely to find an acceptable
solution and is quicker than checking every
possible cycle | B1
[1] | 2.4 | Solution is good enough and method is quick
Accept ‘quicker’ or ‘easier’ or ‘more efficient’, o.e.
Or any of the following o.e.
Algorithmic approach is likely to involve an exhaustive check
Algorithmic approach finds (upper and lower) bounds only (not
necessarily optimal solution)
No known algorithm (currently) (for TSP)
5 | (c) | B 5 C
2 15
6 9
A 4 D
6 7
5
F E | M1
A1
[2] | 1.1
1.1 | Correct arcs (i.e graph correct)
At most one missing or extra arc
Ignore any working for part (f)
Correct network, i.e. correct graph weighted correctly, with no
errors. Allow ambiguous placing if plausibly correct
5 | (d) | A – D – B – C – F
Stalls before visiting E | M1
A1
[2] | 1.1
1.1 | A – D – B – C – F
No E or ‘stall’ or ‘stop’ or other explicit evidence that n.n. does not
reach every vertex
5 | (e) | e.g. A – B – C – F – C – E – D – A
Length = 39(km) | M1
A1
[2] | 3.4
3.4 | Any closed route through all six vertices, using only arcs from QP
Correct length of their route, provided it is less than 50 (km)
5 | (f) | Dijkstra’s algorithm starting from F
A 6 17 B 3 11 C 2 6
17 11 6
D 4 13 E 5 13 F 1 0
21 13 13
F to B = 11 (km) and F to C = 6 (km)
F to A = 17, F to D = 13, F to E = 13 (km) | M1*
A1
M1d*
A1
A1
[5] | 3.1a
1.1
1.1
1.1
1.1 | Evidence of using Dijkstra’s algorithm
May be seen on diagram from part (c)
Need not use box format
Order of labelling not necessary
Using F as the starting vertex
Evidence of updating (at D if starting from F but e.g. at C if starting
from A)
Shortest distance F to B = 11, F to C = 6
Correct in a list or table or seen as permanent labels, o.e.
Shortest distances F to A = 17, F to D = 13, F to E = 13
Correct in a list or table or seen as permanent labels, o.e.
SC
If M0 for dependent method mark (i.e. at best M1 A1 M0) then
SCB1 for all distances correct
F to A = 17, F to B = 11, F to C = 6, F to D = 13, F to E = 13
5 | 13
5 | (g) | A B C D E F
A 6 11 4 9 17
B 6 5 2 7 11
C 11 5 7 7 6
D 4 2 7 5 13
E 9 7 7 5 13
F 17 11 6 13 13 | B1
B1
[2] | 2.1
3.1b | Ignore errors or omissions in row F and column F
Lead diagonal may be blank or ‘0’ or ‘–‘ or similar,
but not contain any non-zero values
Bold values correct (unshaded values excluding row F and col F)
All shaded values correct
5 | (h) | e.g.
BC = 5 B C
BD = 2
DE = 5 D
CF = 6
F E
AD = 4 and AB = 6
(lower bound) 18 + 10
= 28 | M1
M1
A1
[3] | 3.4
2.2a
2.2a | Any spanning tree for {B, C, D, E, F} or {A, B, C, D, E, F}
(need not be MST)
Arcs may be listed (in any order) or tree shown as a diagram
Weights are not necessary here
Use two (different) least weight arcs from A,
for example see AB and AD (and no others) or see 4+6 or see +10
or implied from final answer 28
28 cao from correct MST for {B, C, D, E, F} or {A, B, C, D, E, F}
6 | 11 | 4 | 9 | 17
5
\begin{enumerate}[label=(\alph*)]
\item Write down a way in which the nearest neighbour method can fail to solve the problem of finding a least weight cycle through all the vertices of a network.
\item Explain why, when trying to find a least weight cycle through all the vertices of a network, an ad hoc method may be preferable to an algorithmic approach.

The distance matrix below represents a network connecting six viewpoints $\mathrm { A } , \mathrm { B } , \mathrm { C } , \mathrm { D } , \mathrm { E }$ and F . The distance matrix shows the direct distances between each pair of viewpoints where a direct route exists.\\
The distances are measured in km.\\
A blank shows that there is no direct route between the two viewpoints.

\begin{center}
\begin{tabular}{|l|l|l|l|l|l|l|}
\hline
 & A & B & C & D & E & F \\
\hline
A &  & 6 &  & 4 &  &  \\
\hline
B & 6 &  & 5 & 2 & 9 &  \\
\hline
C &  & 5 &  & 15 & 7 & 6 \\
\hline
D & 4 & 2 & 15 &  & 5 &  \\
\hline
E &  & 9 & 7 & 5 &  &  \\
\hline
F &  &  & 6 &  &  &  \\
\hline
\end{tabular}
\end{center}
\item Draw the network on the vertices given in the Printed Answer Booklet.
\item Apply the nearest neighbour method, starting from A.

A hiker wants to travel between the six viewpoints, starting and finishing at A.\\
The hiker must visit every viewpoint at least once, but may visit a viewpoint more than once.
\item Show that the hiker does not need to travel as far as 50 km .
\item Use an appropriate algorithm to find the shortest distance from F to each of the other viewpoints.
\item Complete the table in the Printed Answer Book to show the shortest distance between each pair of viewpoints.
\item Use your answer to part (g) to find a lower bound for the distance the hiker must travel by initially deleting vertex A.
\end{enumerate}

\hfill \mbox{\textit{OCR Further Discrete 2024 Q5 [18]}}