Results 1 
6 of
6
MultiLevel Partitioning and Distribution of the Assignment Problem for LargeScale MultiRobot Task Allocation
"... Abstract — A team of robots can handle failures and dynamic tasks by repeatedly assigning functioning robots to tasks. This paper introduces an algorithm that scales to large numbers of robots and tasks by exploiting both task locality and sparsity. The algorithm mixes both centralized and decentral ..."
Abstract

Cited by 8 (1 self)
 Add to MetaCart
(Show Context)
Abstract — A team of robots can handle failures and dynamic tasks by repeatedly assigning functioning robots to tasks. This paper introduces an algorithm that scales to large numbers of robots and tasks by exploiting both task locality and sparsity. The algorithm mixes both centralized and decentralized approaches at different scales to produce a fast, robust method that is accurate and scalable, and reduces both the global communication and unnecessary repeated computation. We depart from optimization and bipartite matching formulations of the problem, observing instead that an assignment can be computed through coarsening and partitioning operations on the utility matrix. First, a coarse assignment is calculated by evaluating the global utility information and partitioning it into clusters in a problemdomain independent way. Next, the assignment solutions in each partition are refined (either recursively, or via an existing algorithm). This multilevel framework allows the repeated reassignment to execute among interrelated partitions. The results suggest that only a minor sacrifice in solution quality is required for gains in efficiency. The proposed algorithm is validated using extensive simulation experiments and the results show advantages over the traditional optimal assignment algorithms. I.
Largescale multirobot task allocation via dynamic partitioning and distribution. Autonomous Robots 33(3):291–307
, 2012
"... This paper introduces an approach that scales assignment algorithms to large numbers of robots and tasks. It is especially suitable for dynamic task allocations since both task locality and sparsity can be effectively exploited. We observe that an assignment can be computed through coarsening and ..."
Abstract

Cited by 7 (3 self)
 Add to MetaCart
This paper introduces an approach that scales assignment algorithms to large numbers of robots and tasks. It is especially suitable for dynamic task allocations since both task locality and sparsity can be effectively exploited. We observe that an assignment can be computed through coarsening and partitioning operations on the standard utility matrix via a set of mature partitioning techniques and programs. The algorithm mixes centralized and decentralized approaches dynamically at different scales to produce a fast, robust method that is accurate and scalable, and reduces both the global communication and unnecessary repeated computation. An allocation results by operating on each partition: either the steps are repeated recursively to refine the generalized assignment, or each subproblem may be solved by an existing algorithm. The results suggest that only a minor sacrifice in solution quality is needed for significant gains in efficiency. The algorithm is validated using extensive simulation experiments and the results show advantages over the traditional optimal assignment algorithms.
BranchandCut for a Semidefinite Relaxation of Largescale Minimum Bisection Problems
, 2007
"... ..."
A Continuous Characterization of Maximal Cliques in kuniform Hypergraphs
"... Abstract. In 1965 Motzkin and Straus established a remarkable connection between the local/global maximizers of the Lagrangian of a graph G over the standard simplex ∆ and the maximal/maximum cliques of G. In this work we generalize the MotzkinStraus theorem to kuniform hypergraphs, establishing a ..."
Abstract

Cited by 6 (1 self)
 Add to MetaCart
(Show Context)
Abstract. In 1965 Motzkin and Straus established a remarkable connection between the local/global maximizers of the Lagrangian of a graph G over the standard simplex ∆ and the maximal/maximum cliques of G. In this work we generalize the MotzkinStraus theorem to kuniform hypergraphs, establishing an isomorphism between local/global minimizers of a particular function over ∆ and the maximal/maximum cliques of a kuniform hypergraph. This theoretical result opens the door to a wide range of further both practical and theoretical applications, concerning continuousbased heuristics for the maximum clique problem on hypergraphs, as well as the discover of new bounds on the clique number of hypergraphs. Moreover we show how the continuous optimization task related to our theorem, can be easily locally solved by mean of a dynamical system. 1
Recent advances in graph partitioning
, 2013
"... We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions. ..."
Abstract

Cited by 6 (2 self)
 Add to MetaCart
We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions.
Course Notes: Graph Partitioning and Graph Clustering in Theory and Practice
, 2015
"... I worked on partitioning and clustering problems for almost seven years now. Yet, I still find these problems incredibly fascinating, there is so much work to be done and the field is evolving at such an high pace. I am really glad to be able to work on such interesting topics and hope that I can co ..."
Abstract
 Add to MetaCart
(Show Context)
I worked on partitioning and clustering problems for almost seven years now. Yet, I still find these problems incredibly fascinating, there is so much work to be done and the field is evolving at such an high pace. I am really glad to be able to work on such interesting topics and hope that I can convince or at least transfer a little bit of my fascination on to you – the reader of this script and/or student of my lecture. The course notes in front of you collect material needed to follow the course “Graph Partitioning and Graph Clustering in Theory and Practice ” which has been first held at the Karlsruhe Institute of Technology (KIT) in the summer of 2014. This script has been mostly created by students attending the lecture in