Lesson DB4-DB5
DB4-DB5 Travelling salesperson bounds and refining network models Quiz: AQA Further Maths, Unit 5
20 questions
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Lesson DB4-DB5, Travelling salesperson bounds and refining network models: 20 multiple choice questions for the AQA Further Maths (7367), Unit 5: Optional application 3: discrete mathematics, written with Revision Ninja.
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The 20 questions
-
What is the travelling salesperson problem (TSP) on a network?
- Finding a route that traverses every arc at least once, repeating arcs if needed
- Finding a minimum spanning tree that connects every node to the network
- Finding a minimum-weight closed route that visits every node exactly once and returns to the start
- Finding the route of maximum total weight through the network
-
Which method gives a lower bound for the travelling salesperson problem?
- Delete one node, find a minimum spanning tree of the remaining nodes, then add the two smallest arcs from the deleted node
- Find a Hamiltonian cycle that uses only the greatest-weight arc at each node
- Add the two largest arcs from the start node to a minimum spanning tree
- Find a minimum spanning tree and double its total weight
-
Which method gives an upper bound for the travelling salesperson problem?
- Start at a node and repeatedly move to the nearest unvisited node, then return to the start
- Choose the shortest arc in the network and repeat it until every node has been visited
- Delete each node in turn and find a minimum spanning tree of the remaining network
- Start at the node of greatest degree and always move along the longest arc available
-
A network's lower bound for the travelling salesperson problem is 18, and a nearest neighbour tour has weight 20. What can be said about the optimal tour weight?
- It is exactly 19
- It is at least 20
- It lies between 18 and 20 inclusive
- It is at most 18
-
A complete network has nodes A, B, C, D, E with arc weights AB=4, AC=6, AD=5, AE=7, BC=3, BD=8, BE=6, CD=4, CE=5 and DE=2. Deleting node A leaves nodes B, C, D and E, whose minimum spanning tree has weight 9. What is the lower bound for the travelling salesperson problem?
- 20
- 9
- 18
- 13
-
A complete network has nodes A, B, C, D, E with arc weights AB=4, AC=6, AD=5, AE=7, BC=3, BD=8, BE=6, CD=4, CE=5 and DE=2. Using the nearest neighbour method starting at A, the tour is A-B-C-D-E-A. What is its total weight?
- 18
- 19
- 20
- 22
-
A complete network has nodes A, B, C, D, E with arc weights AB=4, AC=6, AD=5, AE=7, BC=3, BD=8, BE=6, CD=4, CE=5 and DE=2. What is the total weight of the tour A-B-C-E-D-A?
- 21
- 19
- 20
- 18
-
Why is the lower bound method valid for the travelling salesperson problem?
- A minimum spanning tree is itself a tour, so its weight equals the travelling salesperson optimum
- The lower bound uses the largest arcs, which must be included in every tour
- A tour minus one node's two arcs is a spanning tree of the others, so the tour weighs at least the MST plus the two smallest arcs
- A Hamiltonian cycle always has the same weight as the minimum spanning tree of the network
-
How many distinct Hamiltonian cycles does a complete network on 6 nodes have, treating a cycle and its reverse as the same?
- 720
- 60
- 30
- 120
-
Which approach improves an upper bound for the travelling salesperson problem found by the nearest neighbour method?
- Use the maximum-weight arc at each step to avoid short cycles
- Delete the node with the fewest arcs and repeat the method on the rest
- Replace every arc weight with its reciprocal and repeat the method
- Repeat the nearest neighbour method from different starting nodes and keep the tour of least weight
-
A network model is refined by adding a new arc between two nodes that were not previously joined. What is the effect on the optimal travelling salesperson tour?
- The new arc always becomes part of the minimum spanning tree and must be deleted
- The optimal tour weight can stay the same or fall, but cannot rise, because more routes become available
- The optimal tour weight always rises, because the network is larger
- The optimal tour weight never changes, because tours use only existing arcs
-
In a refined network model, how is a one-way street best represented?
- By doubling the weight of every arc that joins the street's two ends
- By two undirected arcs of equal weight
- By removing the node at the end of the street from the network
- By a directed arc, so that travel is allowed only in the permitted direction
-
If deleting a node gives a minimum spanning tree of weight W on the remaining nodes, and the two smallest arcs at the deleted node have weights a and b, what is the lower bound for the travelling salesperson problem?
- W + a + b
- 2W + a + b
- W + a - b
- W + 2a + 2b
-
A travelling salesperson problem has lower bound 31 and a nearest neighbour tour of weight 38. Which statement is correct?
- The gap between the bounds is 69, found by adding the lower and upper bounds
- The optimal tour weight is at most 31, because the lower bound is an upper bound
- The optimal tour weight is exactly 38, because nearest neighbour is always optimal
- The optimal tour weight lies between 31 and 38, so the gap between the bounds is 7
-
A road network model assumes fixed travel times, but traffic varies during the day. Which refinement is valid?
- Replace the fixed arc weights with time-dependent weights reflecting traffic at the relevant time of day
- Ignore every node of degree 2, since it does not affect the route
- Use the average of all arc weights for every arc in the network
- Remove every arc except those on a minimum spanning tree
-
A node in a network has degree 1. What does this imply for the travelling salesperson problem?
- The minimum spanning tree must exclude this node
- The nearest neighbour tour must use this node twice
- No Hamiltonian cycle exists, because a tour must use two different arcs at every node
- The lower bound must be zero, since the node adds no weight
-
Why might the lower bound for the travelling salesperson problem be strictly less than the optimal tour weight?
- The bound always uses an arc counted twice, which inflates the optimum
- The bound comes from a relaxed problem, so it need not correspond to any actual tour
- The bound is always the weight of a Hamiltonian cycle that is not optimal
- The bound is always greater than the optimum, so it can never be strictly less
-
A complete network has nodes A, B, C, D, E with arc weights AB=4, AC=6, AD=5, AE=7, BC=3, BD=8, BE=6, CD=4, CE=5 and DE=2. Using the nearest neighbour method starting at C, the tour found is C-B-A-D-E-C. What is its total weight?
- 18
- 22
- 19
- 20
-
Which statement best describes the role of the lower and upper bounds for the travelling salesperson problem?
- They guarantee that the nearest neighbour tour is the optimal tour
- They remove the need to calculate any tour at all
- They show that the lower bound is always exactly the optimum
- They show how close a found tour is to optimal, since the true optimum lies between the lower and upper bounds
-
How many distinct Hamiltonian cycles does a complete network on 5 nodes have, treating a cycle and its reverse as the same?
- 120
- 24
- 6
- 12
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