<p><i>Path cover</i> is one of the well-known NP-hard problems that has received much attention. In this paper, we study a variant of path cover, denoted by <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10878_2025_1279_Article_IEq3.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="54" /> </InlineMediaObject> <EquationSource Format="TEX">\(\hbox {MPC}^{{4}+}_v\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mtext>MPC</mtext> <mi>v</mi> <mrow> <mn>4</mn> <mo>+</mo> </mrow> </msubsup> </math></EquationSource> </InlineEquation>, to cover as many vertices in a given graph <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10878_2025_1279_Article_IEq4.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="81" /> </InlineMediaObject> <EquationSource Format="TEX">\(G = (V, E)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>G</mi> <mo>=</mo> <mo stretchy="false">(</mo> <mi>V</mi> <mo>,</mo> <mi>E</mi> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> as possible by a collection of vertex-disjoint paths each of order four or above. The problem admits an existing <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10878_2025_1279_Article_IEq5.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="57" /> </InlineMediaObject> <EquationSource Format="TEX">\(O(|V|^8)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>O</mi> <mo stretchy="false">(</mo> <mo stretchy="false">|</mo> <mi>V</mi> <msup> <mo stretchy="false">|</mo> <mn>8</mn> </msup> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation>-time 2-approximation algorithm by applying several time-consuming local improvement operations (Gong et al.: Proceedings of MFCS 2022, LIPIcs 241, pp 53:1–53:14, 2022). In contrast, our new algorithm uses a completely different method and it is an improved <InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10878_2025_1279_Article_IEq6.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="167" /> </InlineMediaObject> <EquationSource Format="TEX">\(O(\min \{|E|^2|V|^2, |V|^5\})\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msup> <mrow> <mi>O</mi> <mo stretchy="false">(</mo> <mo movablelimits="true">min</mo> <mo stretchy="false">{</mo> <mo stretchy="false">|</mo> <mi>E</mi> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <msup> <mrow> <mo stretchy="false">|</mo> <mi>V</mi> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <msup> <mrow> <mo>,</mo> <mo stretchy="false">|</mo> <mi>V</mi> <mo stretchy="false">|</mo> </mrow> <mn>5</mn> </msup> <mrow> <mo stretchy="false">}</mo> <mo stretchy="false">)</mo> </mrow> </mrow> </math></EquationSource> </InlineEquation>-time 1.874-approximation algorithm, which answers the open question in Gong et al. (2022) in the affirmative. An important observation leading to the improvement is that the number of vertices in a maximum matching <i>M</i> of <i>G</i> is relatively large compared to that in an optimal solution of <InlineEquation ID="IEq7"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10878_2025_1279_Article_IEq7.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="54" /> </InlineMediaObject> <EquationSource Format="TEX">\(\hbox {MPC}^{{4}+}_v\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mtext>MPC</mtext> <mi>v</mi> <mrow> <mn>4</mn> <mo>+</mo> </mrow> </msubsup> </math></EquationSource> </InlineEquation>. Our new algorithm forms a feasible solution of <InlineEquation ID="IEq8"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10878_2025_1279_Article_IEq8.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="54" /> </InlineMediaObject> <EquationSource Format="TEX">\(\hbox {MPC}^{{4}+}_v\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mtext>MPC</mtext> <mi>v</mi> <mrow> <mn>4</mn> <mo>+</mo> </mrow> </msubsup> </math></EquationSource> </InlineEquation> from a maximum matching <i>M</i> by computing a maximum-weight path-cycle cover in an auxiliary graph to connect as many edges in <i>M</i> as possible.</p>

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An improved approximation algorithm for covering vertices by \(4^+\)-paths

  • Mingyang Gong,
  • Zhi-Zhong Chen,
  • Guohui Lin,
  • Lusheng Wang

摘要

Path cover is one of the well-known NP-hard problems that has received much attention. In this paper, we study a variant of path cover, denoted by \(\hbox {MPC}^{{4}+}_v\) MPC v 4 + , to cover as many vertices in a given graph \(G = (V, E)\) G = ( V , E ) as possible by a collection of vertex-disjoint paths each of order four or above. The problem admits an existing \(O(|V|^8)\) O ( | V | 8 ) -time 2-approximation algorithm by applying several time-consuming local improvement operations (Gong et al.: Proceedings of MFCS 2022, LIPIcs 241, pp 53:1–53:14, 2022). In contrast, our new algorithm uses a completely different method and it is an improved \(O(\min \{|E|^2|V|^2, |V|^5\})\) O ( min { | E | 2 | V | 2 , | V | 5 } ) -time 1.874-approximation algorithm, which answers the open question in Gong et al. (2022) in the affirmative. An important observation leading to the improvement is that the number of vertices in a maximum matching M of G is relatively large compared to that in an optimal solution of \(\hbox {MPC}^{{4}+}_v\) MPC v 4 + . Our new algorithm forms a feasible solution of \(\hbox {MPC}^{{4}+}_v\) MPC v 4 + from a maximum matching M by computing a maximum-weight path-cycle cover in an auxiliary graph to connect as many edges in M as possible.