Approximation algorithms for the bi-criteria weighted MAX-CUT problem

Authors:
Eric Angel;Evripidis Bampis;Laurent Gourvès
Affiliations:
LaMI, CnRS UMR 8042, Université d'Évry Val d'Essonne, France;LaMI, CnRS UMR 8042, Université d'Évry Val d'Essonne, France;LaMI, CnRS UMR 8042, Université d'Évry Val d'Essonne, France
Venue:
WG'05 Proceedings of the 31st international conference on Graph-Theoretic Concepts in Computer Science
Year:
2005

Citing 9
Cited 0

An application of combinatorial optimization to statistical physics and circuit layout design

Operations Research
.879-approximation algorithms for MAX CUT and MAX 2SAT

STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming

Journal of the ACM (JACM)
Improved bicriteria existence theorems for scheduling

Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Algorithmics for hard problems: introduction to combinatorial optimization, randomization, approximation, and heuristics

Algorithmics for hard problems: introduction to combinatorial optimization, randomization, approximation, and heuristics
Existence theorems, lower bounds and algorithms for scheduling to meet two objectives

SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
On the approximability of trade-offs and optimal access of Web sources

FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Multicriteria Optimization

Multicriteria Optimization
On the existence of schedules that are near-optimal for both makespan and total weighted completion time

Operations Research Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

We consider a generalization of the classical max-cut problem where two objective functions are simultaneously considered. We derive some theorems on the existence and the non-existence of feasible cuts that are at the same time near optimal for both criteria. Furthermore, two approximation algorithms with performance guarantee are presented. The first one is deterministic while the second one is randomized.