An approximation algorithm based on chain implication for constrained minimum vertex covers in bipartite graphs

Authors:
Jianxin Wang;Xiaoshuang Xu;Jianer Chen
Affiliations:
School of Information Science and Engineering, Central South University, Changsha, China;School of Information Science and Engineering, Central South University, Changsha, China;School of Information Science and Engineering, Central South University, Changsha, China and Department of Computer Science Texas A&M University, College Station, TX
Venue:
TAMC'07 Proceedings of the 4th international conference on Theory and applications of models of computation
Year:
2007

Citing 9
Cited 0

Principles of artificial intelligence

Principles of artificial intelligence
Complexity of Fault Diagnosis in Comparison Models

IEEE Transactions on Computers
A New Class Of Efficient Algorithms For Reconfiguration Of Memory Arrays

IEEE Transactions on Computers
Generation of Minimal Vertex Covers for Row/Column Allocation in Self-Repairable Arrays

IEEE Transactions on Computers
An efficient exact algorithm for constraint bipartite vertex cover

Journal of Algorithms
Introduction to Algorithms

Introduction to Algorithms
Constrained minimum vertex cover in bipartite graphs: complexity and parameterized algorithms

Journal of Computer and System Sciences - Special issue on Parameterized computation and complexity
Efficient Spare Allocation for Reconfigurable Arrays

IEEE Design & Test
Parameterized Complexity

Parameterized Complexity

Quantified Score

Hi-index	0.00

Visualization

Abstract

The constrained minimum vertex cover problem on bipartite graphs (the Min-CVCB problem) is an NP-complete problem. This paper presents a polynomial time approximation algorithm for the problem based on the technique of chain implication. For any given constant Ɛ 0, if an instance of the Min-CVCB problem has a minimum vertex cover of size (ku, kl), our algorithm constructs a vertex cover of size (ku*, kl* ), satisfying max{ku*/ku, kl* /kl} ≤ 1 + Ɛ.