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6 Approximation and Randomized Algorithm

Approximation​

An optimization (minimization) problem is called ϵ\epsilon-approximable if there exists a polynomial time algorithm that outputs a solution of cost CC, when the optimal cost is C∗C^*, and CC∗≤ϵ\frac{C}{C^*}\leq \epsilon or C∗C≤ϵ\frac{C^*}C\leq \epsilon

Randomized Algorithm​

  • Monte Carlo: runs in polynomial time always and output is correct with high probability
  • Las Vegas: runs in expected polynomial time and output always correct