While using the K$-$means algorithm, what are some ways to avoid getting stuck at a local optimum?

Run the algorithm multiple times using different random initializations, and take the optimum.

Run the algorithm multiple times with the same initialization, and take the optimum.

Use a smarter initialization like K$-$means$++.$

Initialize using a previous run of K$-$means.