Efficient Robust Algorithms for the Maximum Weight Stable Set Problem in Chair-free Graph Classes

Modular decomposition of graphs is a powerful tool for designing efficient algorithms for algorithmic graph problems such as the Maximum Weight Stable Set Problem and the Maximum Weight Clique Problem. Using this tool we obtain O(nm) time algorithms for the Maximum Weight Stable Set Problem on (chair, co-P)-free, (chair,P5)-free and (chair,bull)-free graphs. Moreover, our algorithms are robust in the sense that we do not have to check in advance whether the input graphs are indeed (chair, co-P)-free or (chair,P5)-free or (chair,bull)-free

Efficient robust algorithms for the Maximum Weight Stable Set problem in chair-free graph classes

Modular decomposition of graphs is a powerful tool for designing efficient algorithms for problems on graphs such as Maximum Weight Stable Set (MWS) and Maximum Weight Clique. Using this tool we obtain O(n · m) time algorithms for MWS on chair- and xbull-free graphs which considerably extend an earlier result on bull- and chair-free graphs by De Simone and Sassano (the chair is the graph with vertices a,b,c,d,e and edges ab,bc,cd,be,andthexbull is the graph with vertices a, b, c, d, e, f and edges ab, bc, cd, de, bf, cf). Moreover, our algorithm is robust in the sense that we do not have to check in advance whether the input graphs are indeed chair- and xbull-free. © 2003 Elsevier B.V. All rights reserved

Efficient Robust Algorithms for the Maximum Weight Stable Set Problem in Chair-free Graph Classes

Modular decomposition of graphs is a powerful tool for designing efficient algorithms for problems on graphs such as Maximum Weight Stable Set (MWS) and Maximum Weight Clique. Using this tool we obtain O(n·m) time algorithms for MWS on chair- and xbull-free graphs which considerably extends an earlier result on bull- and chair-free graphs by De Simone and Sassano (the chair is the graph with vertices a, b, c, d, e and edges ab, bc, cd, be, and the xbull is the graph with vertices a, b, c, d, e, f and edges ab, bc, cd, de, bf, cf). Moreover, our algorithm is robust in the sense that we do not have to check in advance whether the input graphs are indeed chair- and xbull-free