Consider the following local search approximation algorithm for the unweighted max cut problem: start with an arbitrary partition of the vertices of the given graph $G = (V,E) $, and as long as you can move 1 or 2 vertices from one side of the partition to the other, or switch between 2 vertices on opposite sides of the partition, in a way that improves the cut, do so.
I know that this algorithm is a 2-approximation algorithm. I want to prove that this approximation is tight. That is, the algorithm is not an $\alpha$-approximation algorithm for any $\alpha < 2$ .
I found an example for the tightness of the "regular" local search approximation algorithm of max-cut, where at each iteration, you can move only 1 vertex from one side of the partition to the other, and can't switch between two vertices on opposite sides. The example is of the complete bipartite graph $ K_{2n,2n} $. If the initial cut includes $n$ vertices from each side of the graph in each side of the partition, the cut will include half of the edges, while the optimal cut will include all of them. The "regular" algorithm will not be able to improve the cut from this initial position.
However, this example doesn't work for the algorithm described on top, because we can improve the cut by switching between two vertices from opposite sides of the partition.
Can someone please describe an example or a give clue for an example that can prove that the approximation is tight? Thanks.