Abstract
Given a graph with non-negative edge weights, the MAX CUT problem is to partition the set of vertices into two subsets so that the sum of the weights of edges with endpoints in different subsets is maximised. This classical NP-hard problem finds applications in VLSI design, statistical physics, and classification among other fields. This paper compares the performance of several greedy construction heuristics for MAX-CUT problem. In particular, a new 'worst-out' approach is studied and the proposed edge contraction heuristic is shown to have an approximation ratio of at least 1/3. The results of experimental comparison of the worst-out approach, the well-known best-in algorithm, and modifications for both are also included.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Computational Science and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
