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Shortest Paths: Permutations & Combinations Video Lecture | Quantitative Aptitude (Quant) - CAT
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FAQs on Shortest Paths: Permutations & Combinations Video Lecture - Quantitative Aptitude (Quant) - CAT
| 1. What are permutations and combinations? |  |
Ans. Permutations and combinations are mathematical concepts used to count and calculate the number of possible outcomes in a given scenario. Permutations refer to the arrangement of objects in a specific order, while combinations refer to the selection of objects without considering their order.
| 2. How do permutations and combinations relate to the shortest paths problem? | |
Ans. In the context of the shortest paths problem, permutations and combinations are used to calculate the number of possible paths between two points. By considering the different arrangements or selections of vertices, we can determine all the potential paths and find the shortest one among them.
| 3. What techniques can be used to find the shortest paths using permutations and combinations? | |
Ans. There are several techniques to find the shortest paths using permutations and combinations. One common approach is to use algorithms like Dijkstra's algorithm or Bellman-Ford algorithm, which utilize permutations and combinations to explore all possible paths and identify the shortest one based on certain criteria such as distance or weight.
| 4. Can permutations and combinations be applied to any graph or network? | |
Ans. Yes, permutations and combinations can be applied to any graph or network, as long as there are defined connections or edges between vertices. Whether it is a simple graph, a directed graph, or a weighted graph, permutations and combinations can be used to analyze and compute the shortest paths between different vertices.
| 5. Are there any limitations or constraints when using permutations and combinations for the shortest paths problem? | |
Ans. While permutations and combinations are powerful tools for finding shortest paths, there are certain constraints and limitations to consider. For example, in larger graphs or networks, the number of possible paths can be exponentially large, making it computationally expensive to calculate all of them. Additionally, the presence of negative cycles in a graph can affect the accuracy and validity of the shortest path calculations.
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Dec 22, 2024 Last updated |
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