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Quentin Vermande

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2

AAAI Conference 2022 Conference Paper

Maximizing Nash Social Welfare in 2-Value Instances

  • Hannaneh Akrami
  • Bhaskar Ray Chaudhury
  • Martin Hoefer
  • Kurt Mehlhorn
  • Marco Schmalhofer
  • Golnoosh Shahkarami
  • Giovanna Varricchio
  • Quentin Vermande

We consider the problem of maximizing the Nash social welfare when allocating a set G of indivisible goods to a set N of agents. We study instances, in which all agents have 2-value additive valuations: The value of every agent i ∈ N for every good j ∈ G is vij ∈ {p, q}, for p, q ∈ N, p ≤ q. In this work, we design an algorithm to compute an optimal allocation in polynomial time if p divides q, i. e. , when p = 1 and q ∈ N after appropriate scaling. The problem is NP-hard whenever p and q are coprime and p ≥ 3. In terms of approximation, we present positive and negative results for general p and q. We show that our algorithm obtains an approximation ratio of at most 1. 0345. Moreover, we prove that the problem is APX-hard, with a lower bound of 1. 000015 achieved at p/q = 4/5.

TCS Journal 2022 Journal Article

Physarum-inspired multi-commodity flow dynamics

  • Vincenzo Bonifaci
  • Enrico Facca
  • Frederic Folz
  • Andreas Karrenbauer
  • Pavel Kolev
  • Kurt Mehlhorn
  • Giovanna Morigi
  • Golnoosh Shahkarami

In wet-lab experiments, the slime mold Physarum polycephalum has demonstrated its ability to tackle a variety of computing tasks, among them the computation of shortest paths and the design of efficient networks. For the shortest path problem, a mathematical model for the evolution of the slime is available and it has been shown in computer experiments and through mathematical analysis that the dynamics solves the shortest path problem. In this paper, we generalize the dynamics to the network design problem. We formulate network design as the problem of constructing a network that efficiently supports a multi-commodity flow problem. We investigate the dynamics in computer simulations and analytically. The simulations show that the dynamics is able to construct efficient and elegant networks. In the theoretical part we show that the dynamics minimizes an objective combining the cost of the network and the cost of routing the demands through the network. We also give alternative characterizations of the optimum solution.

v2026.09.13