Algorithm 4.

formCluster(W, n)

Require: Original dataset D, trajectory W, integer n specifying the   number of trajectories to be included in the cluster
Return: Cluster C, ILM(C) and ALM(C)
1:	D ← D \ {W}; W̃ ← W; i′ ← 0; a′ ← 0
2:	for all j ∈ [1, (n − 1)] do
3:	Z ← argminT∈D {(i + a)|i, a ∈ A-GS(W̃, i′, a′, T)}   ▷Align W̃ with Z, the closest trajectory to W̃
4:	{T̃, i, a} ← A-GS(W̃, i′, a′, Z)
5:	D ← D \ {Z}; W̃ ← T; i′ ← i; a′ ← a
6:	end for ▷Form a cluster of anonymized trajectories
7:	C ← the set containing n copies of W̃
8:	return {C, i′, a′}