On Approximation of Robust Max-Cut and Related Problems using Randomized Rounding Algorithms

June 04, 2024 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Haoyan Shi, Sanjay Mehrotra arXiv ID 2406.01856 Category cs.DS: Data Structures & Algorithms Cross-listed math.OC Citations 0 Venue arXiv.org Last Checked 5 months ago
Abstract
Goemans and Williamson proposed a randomized rounding algorithm for the MAX-CUT problem with a 0.878 approximation bound in expectation. The 0.878 approximation bound remains the best-known approximation bound for this APX-hard problem. Their approach was subsequently applied to other related problems such as Max-DiCut, MAX-SAT, and Max-2SAT, etc. We show that the randomized rounding algorithm can also be used to achieve a 0.878 approximation bound for the robust and distributionally robust counterparts of the max-cut problem. We also show that the approximation bounds for the other problems are maintained for their robust and distributionally robust counterparts if the randomization projection framework is used.
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