Improving the Integrality Gap for Multiway Cut

07/25/2018
∙
by   Kristóf Bérczi, et al.
∙
0
∙

In the multiway cut problem, we are given an undirected graph with non-negative edge weights and a collection of k terminal nodes, and the goal is to partition the node set of the graph into k non-empty parts each containing exactly one terminal so that the total weight of the edges crossing the partition is minimized. The multiway cut problem for k> 3 is APX-hard. For arbitrary k, the best-known approximation factor is 1.2965 due to [Sharma and Vondrák, 2014] while the best known inapproximability factor is 1.2 due to [Angelidakis, Makarychev and Manurangsi, 2017]. In this work, we improve on the lower bound to 1.20016 by constructing an integrality gap instance for the CKR relaxation. A technical challenge in improving the gap has been the lack of geometric tools to understand higher-dimensional simplices. Our instance is a non-trivial 3-dimensional instance that overcomes this technical challenge. We analyze the gap of the instance by viewing it as a convex combination of 2-dimensional instances and a uniform 3-dimensional instance. We believe that this technique could be exploited further to construct instances with larger integrality gap. One of the byproducts from our proof technique is a generalization of a result on Sperner admissible labelings due to [Mirzakhani and Vondrák, 2015] that might be of independent combinatorial interest.

READ FULL TEXT

Please sign up or login with your details

Continue with:
Or login with email
Enter Password
Re-enter Password

Forgot password? Click here to reset
Success!
Error Icon An error occurred

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×
Pro

Consider DeepAI Pro

Subscribe to DeepAI Pro
DeepAI Pro
Provides a limited generation allowance each month. When exceeded, you are charged overage rates available at deepai.org/pricing. Also includes an ad-free experience and API access. Renews automatically until canceled. Non-refundable.
Subtotal
Total due today

Payment

Add DeepAI credits
DeepAI credits
One-time purchase. Credits are added to your wallet after payment.
Subtotal
Total due today

Payment