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# A 21/16-Approximation for the Minimum 3-Path Partition Problem

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LIPIcs.ISAAC.2019.46.pdf
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## Cite As

Yong Chen, Randy Goebel, Bing Su, Weitian Tong, Yao Xu, and An Zhang. A 21/16-Approximation for the Minimum 3-Path Partition Problem. In 30th International Symposium on Algorithms and Computation (ISAAC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 149, pp. 46:1-46:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.ISAAC.2019.46

## Abstract

The minimum k-path partition (Min-k-PP for short) problem targets to partition an input graph into the smallest number of paths, each of which has order at most k. We focus on the special case when k=3. Existing literature mainly concentrates on the exact algorithms for special graphs, such as trees. Because of the challenge of NP-hardness on general graphs, the approximability of the Min-3-PP problem attracts researchers' attention. The first approximation algorithm dates back about 10 years and achieves an approximation ratio of 3/2, which was recently improved to 13/9 and further to 4/3. We investigate the 3/2-approximation algorithm for the Min-3-PP problem and discover several interesting structural properties. Instead of studying the unweighted Min-3-PP problem directly, we design a novel weight schema for l-paths, l in {1, 2, 3}, and investigate the weighted version. A greedy local search algorithm is proposed to generate a heavy path partition. We show the achieved path partition has the least 1-paths, which is also the key ingredient for the algorithms with ratios 13/9 and 4/3. When switching back to the unweighted objective function, we prove the approximation ratio 21/16 via amortized analysis.

## Subject Classification

##### ACM Subject Classification
• Mathematics of computing → Graph algorithms
• Mathematics of computing → Approximation algorithms
• Theory of computation → Graph algorithms analysis
• Theory of computation → Approximation algorithms analysis
##### Keywords
• 3-path partition
• exact set cover
• approximation algorithm
• local search
• amortized analysis

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## References

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