Chen, J., Nöllenburg, M., Simola, S., Villedieu, A., & Wallinger, M. (2022). Multidimensional Manhattan Preferences. In LATIN 2022: Theoretical Informatics (pp. 273–289). https://doi.org/10.1007/978-3-031-20624-5_17
A preference profile (i.e., a collection of linear preference
orders of the voters over a set of alternatives) with m alternatives and
n voters is d-Manhattan (resp. d-Euclidean) if both the alternatives and
the voters can be placed into a d-dimensional space such that between
each pair of alternatives, every voter prefers the one which has a shorter
Manhattan (resp. Euclidean) distance to the voter.
We initiate the study of how d-Manhattan preference profiles depend on
the values m and n. First, we provide explicit constructions to show that
each preference profile with m alternatives and n voters is d-Manhattan
whenever d ≥ min(n, m − 1). Second, for d = 2, we show that the smallest
non d-Manhattan preference profile has either 3 voters and 6 alternatives,
or 4 voters and 5 alternatives, or 5 voters and 4 alternatives. This is more
complex than the case with d-Euclidean preferences (see [Bogomolnaia and
Laslier, 2007] and [Bulteau and Chen, 2022]).