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.
@InProceedings{chen_et_al:LIPIcs.ISAAC.2019.46, author = {Chen, Yong and Goebel, Randy and Su, Bing and Tong, Weitian and Xu, Yao and Zhang, An}, title = {{A 21/16-Approximation for the Minimum 3-Path Partition Problem}}, booktitle = {30th International Symposium on Algorithms and Computation (ISAAC 2019)}, pages = {46:1--46:20}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-130-6}, ISSN = {1868-8969}, year = {2019}, volume = {149}, editor = {Lu, Pinyan and Zhang, Guochuan}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2019.46}, URN = {urn:nbn:de:0030-drops-115422}, doi = {10.4230/LIPIcs.ISAAC.2019.46}, annote = {Keywords: 3-path partition, exact set cover, approximation algorithm, local search, amortized analysis} }
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