Arrow Research search

Author name cluster

Jochen Könemann

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

13 papers
2 author rows

Possible papers

13

TCS Journal 2024 Journal Article

On the complexity of nucleolus computation for bipartite b-matching games

  • Jochen Könemann
  • Justin Toth
  • Felix Zhou

We explore the complexity of nucleolus computation in b-matching games on bipartite graphs. We show that computing the nucleolus of a simple b-matching game is NP -hard when b ≡ 3 even on bipartite graphs of maximum degree 7. We complement this with partial positive results in the special case where b values are bounded by 2. In particular, we describe an efficient algorithm when a constant number of vertices satisfy b v = 2 as well as an efficient algorithm for computing the non-simple b-matching nucleolus when b ≡ 2.

SODA Conference 2018 Conference Paper

Approximating Weighted Tree Augmentation via Chvátal-Gomory Cuts

  • Samuel Fiorini
  • Martin Groß 0001
  • Jochen Könemann
  • Laura Sanità

The weighted tree augmentation problem (WTAP) is a fundamental network design problem. We are given an undirected tree G = ( V, E ) with n = | V | nodes, an additional set of edges L called links and a cost vector. The goal is to choose a minimum cost subset S ⊆ L such that G = ( V, E ∪ S ) is 2-edgeconnected. In the unweighted case, that is, when we have c ℓ = 1 for all ℓ ∊ L, the problem is called the tree augmentation problem (TAP). Both problems are known to be APX-hard, and the best known approximation factors are 2 for WTAP by (Frederickson and JáJá, ’81) and for TAP due to (Kortsarz and Nutov, TALG ’16). Adjashvili (SODA ’17) recently presented an ≈ 1. 96418 + ε -approximation algorithm for WTAP for the case where all link costs are bounded by a constant. This is the first approximation with a better guarantee than 2 that does not require restrictions on the structure of the tree or the links. In this paper, we improve Adjiashvili's approximation to a + ε -approximation for WTAP under the bounded cost assumption. We achieve this by introducing a strong LP that combines {0, ½}-Chvátal-Gomory cuts for the standard LP for the problem with bundle constraints from Adjiashvili. We show that our LP can be solved efficiently and that it is exact for some instances that arise at the core of Adjiashvili's approach. This results in the improved performance guarantee of + ε, which is asymptotically on par with the result by Kortsarz and Nutov. Our result also is the best-known LP-relative approximation algorithm for TAP.

TCS Journal 2014 Journal Article

Social exchange networks with distant bargaining

  • Konstantinos Georgiou
  • George Karakostas
  • Jochen Könemann
  • Zuzanna Stamirowska

Network bargaining is a natural extension of the classical, 2-player Nash bargaining solution to the network setting. Here one is given an exchange network G connecting a set of players V in which edges correspond to potential contracts between their endpoints. In the standard model, a player may engage in at most one contract, and feasible outcomes therefore correspond to matchings in the underlying graph. Kleinberg and Tardos [STOC'08] recently proposed this model, and introduced the concepts of stability and balance for feasible outcomes. The authors characterized the class of instances that admit such solutions, and presented a polynomial-time algorithm to compute them. In this paper, we generalize the work of Kleinberg and Tardos by allowing agents to engage into more complex contracts that span more than two agents. We provide suitable generalizations of the above stability and balance notions, and show that many of the previously known results for the matching case extend to our new setting. In particular, we can show that a given instance admits a stable outcome only if it also admits a balanced one. Like Bateni et al. [ICALP'10] we exploit connections to cooperative games. We fully characterize the core of these games, and show that checking its non-emptiness is NP-complete. On the other hand, we provide efficient algorithms to compute core elements for several special cases of the problem, making use of compact linear programming formulations.

FOCS Conference 2013 Conference Paper

An LMP O(log n)-Approximation Algorithm for Node Weighted Prize Collecting Steiner Tree

  • Jochen Könemann
  • Sina Sadeghian Sadeghabad
  • Laura Sanità

In the node-weighted prize-collecting Steiner tree problem (NW-PCST) we are given an undirected graph G = (V, E), non-negative costs c(u) and penalties π(u) for each u ∈ V. The goal is to find a tree T that minimizes the total cost of the vertices spanned by T plus the total penalty of vertices not in T. This problem is well-known to be set-cover hard to approximate. Moss and Rabani (STOC'01) presented a primal-dual Lagrangean-multiplier-preserving O(ln |V |)-approximation algorithm for this problem. We show a serious problem with the algorithm, and present a new, fundamentally different primal-dual method achieving the same performance guarantee. Our algorithm introduces several novel features to the primal-dual method that may be of independent interest.

SODA Conference 2012 Conference Paper

Weighted capacitated, priority, and geometric set cover via improved quasi-uniform sampling

  • Timothy M. Chan
  • Elyot Grant
  • Jochen Könemann
  • Malcolm Sharpe

The minimum-weight set cover problem is widely known to be O (log n )-approximable, with no improvement possible in the general case. We take the approach of exploiting problem structure to achieve better results, by providing a geometry-inspired algorithm whose approximation guarantee depends solely on an instance-specific combinatorial property known as shallow cell complexity (SCC). Roughly speaking, a set cover instance has low SCC if any column-induced submatrix of the corresponding element-set incidence matrix has few distinct rows. By adapting and improving Varadarajan's recent quasi-uniform random sampling method for weighted geometric covering problems, we obtain strong approximation algorithms for a structurally rich class of weighted covering problems with low SCC. We also show how to derandomize our algorithm. Our main result has several immediate consequences. Among them, we settle an open question of Chakrabarty et al. [8] by showing that weighted instances of the capacitated covering problem with underlying network structure have O (1)-approximations. Additionally, our improvements to Varadarajan's sampling framework yield several new results for weighted geometric set cover, hitting set, and dominating set problems. In particular, for weighted covering problems exhibiting linear (or near-linear) union complexity, we obtain approximability results agreeing with those known for the unweighted case. For example, we obtain a constant approximation for the weighted disk cover problem, improving upon the 2 O (log* n ) -approximation known prior to our work and matching the O (1)-approximation known for the unweighted variant.

STOC Conference 2006 Conference Paper

Simple cost sharing schemes for multicommodity rent-or-buy and stochastic Steiner tree

  • Lisa Fleischer
  • Jochen Könemann
  • Stefano Leonardi 0001
  • Guido Schäfer

In the multi-commodity rent-or-buy network design problem (MRoB) we are given a network together with a set of k terminal pairs R = (s_1, t_1), ..., (s_k, t_k). The goal is to install capacities on the edges of the network so that a prescribed amount of flow f i can be routed between all terminal pairs s i and t i simultaneously. We can either rent capacity on an edge at some cost per unit flow or buy infinite capacity on an edge at some larger fixed cost. The overall objective is to install capacities at a minimum total cost.The version of the stochastic Steiner tree problem (SST) considered here is the Steiner tree problem in the model of two-stage stochastic optimization with recourse. In stage one, there is a known probability distribution on subsets of vertices and we can choose to buy a subset of edges at a given cost. In stage two, a subset of vertices T from the prior known distribution is realized, and additional edges can be bought at a possibly higher cost. The objective is to buy a set of edges in stages one and two so that all vertices in T are connected, and the expected cost is minimized.Gupta et al. (FOCS '03) give a randomized scheme for the MRoB problem that was both used subsequently to improve the approximation ratio for this problem, and extended to yield the best approximation algorithm for SST. One building block of this scheme is a good approximation algorithm for Steiner forests.We present a surprisingly simple 5-approximation algorithm for MRoB and 6-approximation for SST, improving on the best previous guarantees of 6.828 and 12.6, and show that no approximation ratio better than 4.67 can be achieved using the above mentioned randomized scheme in combination with the currently best known Steiner forest approximation algorithms. A key component of our approach are cost shares that are 3-strict for the unmodified primal-dual Steiner forest algorithm.

FOCS Conference 1998 Conference Paper

Faster and Simpler Algorithms for Multicommodity Flow and Other Fractional Packing Problems

  • Naveen Garg 0001
  • Jochen Könemann

This paper considers the problem of designing fast, approximate, combinatorial algorithms for multicommodity flows and other fractional packing problems. We provide a different approach to these problems which yields faster and much simpler algorithms. Our approach also allows us to substitute shortest path computations for min-cost flow computations in computing maximum concurrent flow and min-cost multicommodity flow; this yields much faster algorithms when the number of commodities is large.

v2026.09.13