Deciding how to allocate the seats of a house of representatives is one of the most fundamental problems in the political organization of societies, and has been widely studied over already two centuries. The idea of proportionality is at the core of most approaches to tackle this problem, and this notion is captured by the divisor methods, such as the Jefferson/D'Hondt method. In a seminal work, Balinski and Demange extended the single-dimensional idea of divisor methods to the setting in which the seat allocation is simultaneously determined by two dimensions, and proposed the so-called biproportional apportionment method. The method, currently used in several electoral systems, is however limited to two dimensions and the question of extending it is considered to be an important problem both theoretically and in practice. In this work we initiate the study of multidimensional proportional apportionment. We first formalize a notion of multidimensional proportionality that naturally extends that of Balinski and Demange. By means of analyzing an appropriate integer linear program we are able to prove that, in contrast to the two-dimensional case, the existence of multidimensional proportional apportionments is not guaranteed and deciding its existence is NP-complete. Interestingly, our main result asserts that it is possible to find approximate multidimensional proportional apportionments that deviate from the marginals by a small amount. The proof arises through the lens of discrepancy theory, mainly inspired by the celebrated Beck-Fiala Theorem.We evaluate various methods based of 3-dimensional proportionality, using the data from the recent 2021 Chilean Constitutional Convention election. Besides the classical political and geographical dimensions, this election required the convention to be balanced in gender. The methods we consider are 3-dimensional in spirit but include further characteristics such as plurality constraints and/or minimum quotas for representation.This is joint work with Javier Cembrano, Gonzalo Diaz, and Victor Verdugo. Preliminary versions appeared at EC 2021 and EAAMO 2021.
The hybridizable discontinuous Galerkin (HDG) methods were introduced in the framework of second-order diffusion problems by hybridization and static condensation. We show that the exact solution can be characterized as the solution of local Dirichlet problems (hybridization) which can then be patched together by the transmission conditions (static condensation). Our goal is to show that the HDG methods are nothing but a discrete version of this characterization. To do so, we show that this is also the case for the well-known continuous Galerkin and the mixed methods. We end by sketching how to define HDG methods for general PDEs.