In this question you will explore the Traveling Salesperson Problem (TSP). (a) In every instance (i.e., example) of the TSP, we are given n cities, where each pair of cities is connected by a weighted edge that measures the cost of traveling between those two cities. Our goal is to find the optimal TSP tour, minimizing the total cost of a Hamiltonian cycle in G. Although it is NP-complete to solve the TSP, we found a simple 2-approximation by first generating a minimum-weight spanning tree of G and using this output to determine our TSP tour. Prove that our output is guaranteed to be a 2-approximation, provided the Triangle Inequality holds. In other words, if OP T is the total cost of the optimal solution, and AP P is the total cost of our approximate solution, clearly explain why AP P ≤ 2 × OP T.
In this question you will explore the Traveling Salesperson Problem (TSP).
(a) In every instance (i.e., example) of the TSP, we are given n cities, where each pair of cities is connected by a weighted edge that measures the cost of traveling between those two cities. Our goal is to find the optimal TSP tour, minimizing the total cost of a Hamiltonian cycle in G.
Although it is NP-complete to solve the TSP, we found a simple 2-approximation by first generating a minimum-weight spanning tree of G and using this output to determine our TSP tour.
Prove that our output is guaranteed to be a 2-approximation, provided the Triangle Inequality holds. In other words, if OP T is the total cost of the optimal solution, and AP P is the total cost of our approximate solution, clearly explain why AP P ≤ 2 × OP T.
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