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

Eric Angel (1) , Evripidis Bampis (1) , Laurent Gourvès (1)

1 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes

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. A generalization of these results is given for the bi-criteria MAX-k-CUT problem.

Domains: Computer science; Operations Research [math.OC]; Data Structures and Algorithms [cs.DS]; Discrete Mathematics [cs.DM]; Computer Science and Game Theory [cs.GT]

Eric Angel, Evripidis Bampis, Laurent Gourvès. Approximation algorithms for the bi-criteria weighted MAX-CUT problem. Discrete Applied Mathematics, 2006, 154, pp.1685--1692. ⟨10.1016/j.dam.2006.02.008⟩. ⟨hal-00341345⟩