MCQs

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Overall MCQs for Reference

1. What is the main objective of the Traveling Salesman Problem (TSP)?
   a. Minimize the number of cities visited
   b. Maximize the travel distance
   c. Find the shortest route visiting every city once and returning to the start
   d. Visit every city at least twice
   Answer: cappliedaicourse+1​
2. In TSP, what does “NP-hard” mean?
   a. The problem can be solved in polynomial time
   b. The problem is unsolvable
   c. No known algorithm can solve it efficiently for large instances
   d. The problem has multiple solutions
   Answer: cwikipedia+1​
3. Which of the following is NOT a typical constraint in TSP?
   a. Each city is visited only once
   b. Temporary route stoppage
   c. Return to the starting city
   d. Minimize total travel cost
   Answer: bw3schools+1​
4. What is the brute force solution to TSP?
   a. Try every possible route
   b. Use greedy selection only
   c. Skip cities if needed
   d. Use random selection
   Answer: aappliedaicourse+1​
5. Which AI technique is commonly used for TSP optimization?
   a. Support Vector Machine
   b. Genetic Algorithm
   c. Naive Bayes
   d. Decision Tree
   Answer: btrackobit+1​
6. What does “combinatorial optimization” refer to in TSP?
   a. Optimizing computer speed
   b. Finding a combination of cities for the best route
   c. Combining algorithms for better results
   d. Mixing brute-force and greedy approaches
   Answer: bwikipedia+1​
7. In the classic TSP, which type of graph is used?
   a. Tree
   b. Directed Graph
   c. Undirected Weighted Graph
   d. Unweighted Graph
   Answer: ccsd.uoc+1​
8. What is the goal of “approximation algorithms” in TSP?
   a. Find an exact solution only
   b. Find a possible solution quickly, not necessarily optimal
   c. Solve the problem with unweighted edges
   d. Increase the travel cost
   Answer: bw3schools+1​
9. Which heuristic method selects the nearest unvisited city at each step?
   a. Genetic Algorithm
   b. Greedy Algorithm
   c. Nearest Neighbor Algorithm
   d. Dynamic Programming
   Answer: cappliedaicourse+1​
10. What is the disadvantage of brute-force TSP solutions?
    a. Solutions are always optimal
    b. High computational time for large instances
    c. No route found
    d. Poor route quality
    Answer: bw3schools+1​
11. Which algorithm is known for yielding exact solutions to small TSP instances?
    a. Brute Force
    b. Decision Tree
    c. Random Selection
    d. Support Vector Machine
    Answer: awikipedia+1​
12. What is the main challenge with TSP as cities increase in number?
    a. Decrease in permutations
    b. Exponential growth of possible routes
    c. Linear growth of cost
    d. Simpler route selection
    Answer: blocus+1​
13. Which AI technique is inspired by biological evolution for TSP?
    a. Genetic Algorithm
    b. K-means Clustering
    c. Linear Regression
    d. Naive Bayes
    Answer: atrackobit+1​
14. What does Ant Colony Optimization use to find TSP solutions?
    a. Random guessing
    b. Pheromone trails simulation
    c. Dynamic programming
    d. Reinforcement learning
    Answer: btrackobit+1​
15. In dynamic programming approach for TSP, what does the ‘mask’ represent?
    a. Visited cities
    b. Remaining time
    c. Current route cost
    d. Optimization strategy
    Answer: ageeksforgeeks+1​
16. AI-driven TSP solvers may include which practical factor?
    a. Weather conditions
    b. Fractional distance
    c. Quantum computing only
    d. Ignore real-world limits
    Answer: alocus+1​
17. What is commonly used as input to TSP algorithms?
    a. City names only
    b. Distances between all cities
    c. Total number of cities
    d. Random routes
    Answer: bappliedaicourse+1​
18. Which metaheuristic is not commonly used in TSP?
    a. Simulated Annealing
    b. Random Forest
    c. Genetic Algorithms
    d. Ant Colony Optimization
    Answer: btrackobit+1​
19. Why are greedy algorithms suboptimal for TSP?
    a. They always find the optimal path
    b. They may get trapped in local optima
    c. They consider all routes
    d. They minimize computational time
    Answer: bw3schools+1​
20. What is the output of TSP AI solvers in logistics?
    a. Route sequence and total distance
    b. City names only
    c. Only the number of cities
    d. None of the above
    Answer: alocus+1​
21. Which TSP solution technique uses populations and fitness scores?
    a. Decision Trees
    b. Genetic Algorithms
    c. Brute Force
    d. Greedy Search
    Answer: bappliedaicourse+1​
22. What is a practical application of TSP?
    a. Image classification
    b. Circuit design
    c. Network packet routing
    d. Spam detection
    Answer: blocus+1​
23. What is minimized in Multi-Objective Evolutionary Algorithm (MOEA) for TSP?
    a. Only distance
    b. Travel time and cost
    c. City population
    d. Edge weights only
    Answer: blocus+1​
24. Which approach divides the problem among multiple agents?
    a. Single-agent search
    b. Multi-Agent System
    c. Decision Tree
    d. Linear Regression
    Answer: bappliedaicourse+1​
25. TSP is an important problem in which area of AI?
    a. Object recognition
    b. Combinatorial optimization
    c. Density estimation
    d. Backpropagation
    Answer: bwikipedia+1​
26. Which neural network has been applied to TSP?
    a. Convolutional Neural Network
    b. Hopfield Network
    c. Recurrent Neural Network
    d. Perceptron
    Answer: btrackobit+1​
27. What is the main drawback of using brute-force for TSP on a large scale?
    a. No solution found
    b. Memory overflow
    c. Computational infeasibility
    d. Poor accuracy
    Answer: cwikipedia+1​
28. How does AI help modern enterprises with TSP?
    a. By randomly assigning routes
    b. By ignoring driver skills
    c. By analyzing real-time data and optimizing routes
    d. By fixing travel cost
    Answer: clocus+1​
29. What is the role of historical data in AI TSP solvers?
    a. It’s not used
    b. Minimizes vehicle maintenance
    c. Improves route predictions
    d. Increases travel distance
    Answer: ctrackobit+1​
30. What is the cost matrix in TSP algorithms?
    a. Current route
    b. City age
    c. Table of distances between cities
    d. Table of city populations
    Answer: cgeeksforgeeks+1​
31. Which AI approach for TSP iteratively refines solutions?
    a. Linear Regression
    b. Genetic Algorithm
    c. K-means Clustering
    d. Support Vector Machine
    Answer: bappliedaicourse+1​
32. TSP has applications in which supply-chain management area?
    a. Route optimization
    b. Temperature control
    c. Product labeling
    d. Vendor selection
    Answer: alocus+1​
33. What is another term for the cities in TSP?
    a. Edges
    b. Vertices or nodes
    c. Weights
    d. Branches
    Answer: bcsd.uoc+1​
34. What happens to TSP computational time as cities increase?
    a. Decreases linearly
    b. Remains constant
    c. Increases exponentially
    d. Decreases exponentially
    Answer: cwikipedia+1​
35. Which is a classic dynamic programming TSP algorithm?
    a. Held-Karp
    b. Dijkstra’s Algorithm
    c. Bellman-Ford
    d. A* Search
    Answer: ageeksforgeeks+1​
36. Why can’t brute-force solve large TSP efficiently?
    a. Limited memory
    b. Too many possible routes
    c. Inadequate network bandwidth
    d. Lack of input data
    Answer: bwikipedia+1​
37. Which of the following is NOT an AI method for TSP?
    a. Ant Colony Optimization
    b. Greedy Algorithm
    c. Decision Tree
    d. Simulated Annealing
    Answer: ctrackobit+1​
38. In TSP, what is meant by “return to the starting city”?
    a. End route at random city
    b. Make a path to start after visiting all cities
    c. Never revisit starting city
    d. Start and end at different cities
    Answer: bw3schools+1​
39. Which AI-driven system optimizes TSP schedules in businesses?
    a. Dispatch Management Platform
    b. Image Recognition Software
    c. Sentiment Analysis API
    d. Document Management System
    Answer: aappliedaicourse+1​
40. What is the solution form for TSP?
    a. Sequence of cities
    b. List of city names
    c. Distance matrix
    d. Weighted graph image
    Answer: aw3schools+1​
41. Which of the following is a key complexity in real-world TSPs?
    a. Ignoring traffic
    b. Multiple constraints like time windows and capacity
    c. No constraint at all
    d. Unlimited vehicles
    Answer: blocus+1​
42. Which method simulates heat changes to escape local optima in TSP?
    a. Simulated Annealing
    b. Decision Tree
    c. Greedy Approach
    d. Linear Regression
    Answer: atrackobit+1​
43. What makes route optimization challenging for TSP in AI?
    a. Simple to compute distances
    b. Multiple objectives and constraints
    c. One-dimensional calculation
    d. No actual challenge
    Answer: bappliedaicourse+1​
44. In supply chain, why is TSP relevant?
    a. Only for truck drivers
    b. Optimizes delivery routes and cost
    c. Computes online transactions
    d. Analyzes customer reviews
    Answer: blocus+1​
45. Which is true about neural network approaches to TSP?
    a. Require training on historical data
    b. Always provide exact solutions
    c. Don’t handle large datasets
    d. Never used in practice
    Answer: atrackobit+1​
46. What is the output of an Ant Colony Optimization algorithm in TSP?
    a. Most pheromone-rich path found
    b. Least costly random route
    c. City population order
    d. Route cost ignored
    Answer: aappliedaicourse+1​
47. How does reinforcement learning approach TSP?
    a. By maximizing random selection
    b. By improving route predictions over time
    c. By ignoring past data
    d. By selecting fixed paths only
    Answer: btrackobit+1​
48. Branch and bound approach to TSP helps by:
    a. Pruning suboptimal paths early
    b. Listing all routes sequentially
    c. Ignoring weights
    d. Randomly skipping cities
    Answer: agatevidyalay+1​
49. Which property describes TSP on a graph?
    a. No cycles allowed
    b. Hamiltonian circuit required
    c. No weights allowed
    d. Directed edges always used
    Answer: bcsd.uoc+1​
50. Why is TSP studied in AI?
    a. To solve only mathematical problems
    b. To address real-world optimization challenges
    c. Only for physics applications
    d. For entertainment
    Answer: bwikipedia+2​

1. https://www.appliedaicourse.com/blog/traveling-salesman-problem-in-ai/
2. https://en.wikipedia.org/wiki/Travelling_salesman_problem
3. https://www.w3schools.com/dsa/dsa_ref_traveling_salesman.php
4. https://trackobit.com/blog/what-is-a-traveling-salesman-problem-explained
5. https://www.csd.uoc.gr/~hy583/papers/ch11.pdf
6. https://blog.locus.sh/travelling-salesman-problem/
7. https://www.geeksforgeeks.org/dsa/travelling-salesman-problem-using-dynamic-programming/
8. https://www.gatevidyalay.com/tag/travelling-salesman-problem-ai/
9. https://wayground.com/admin/quiz/5ddf5dd1e4617d001bc08579/travelling-salesman-problem
10. https://www.gatevidyalay.com/tag/travelling-salesman-problem-questions-and-answers/
11. https://www.sanfoundry.com/artificial-intelligence-mcqs-problem-solving-1/
12. https://www.studocu.com/in/quiz/travelling-salesman-problem/5334582
13. https://www.interviewbit.com/blog/travelling-salesman-problem/
14. https://www.tutorialspoint.com/data_structures_algorithms/travelling_salesman_problem.htm
15. https://www.includehelp.com/mcq/discrete-mathematics-dijkstras-algorithm-and-travelling-salesman-problem-mcqs.aspx
16. https://www.youtube.com/watch?v=_xFm4ZWkkkg
17. https://www.youtube.com/watch?v=3QiSyc7KyC4
18. https://www.savemyexams.com/dp/maths/ib/ai/21/hl/revision-notes/geometry-and-trigonometry/graph-theory/travelling-salesman-problem/
19. https://www.geeksforgeeks.org/dsa/traveling-salesman-problem-tsp-implementation/
20. https://study.com/academy/practice/quiz-worksheet-computation-s-traveling-salesman-problem.html