{"title":"Maximum weight t-sparse set problem on vector-weighted graphs","authors":"Yuquan Lin, Wensong Lin","doi":"10.1051/ro/2023145","DOIUrl":null,"url":null,"abstract":"Let t be a nonnegative integer and G = ( V ( G ), E ( G )) be a graph. For v ∈ V ( G ), let N G ( v ) = { u ∈ V ( G ) \\ { v } : uv ∈ E ( G )}. And for S ⊆ V ( G ), we define d S ( G ; v ) = | N G (v) ∩ S | for v ∈ S and d S ( G ; v ) = −1 for v ∈ V ( G ) \\ S . A subset S ⊆ V ( G ) is called a t -sparse set of G if the maximum degree of the induced subgraph G [ S ] does not exceed t . In particular, a 0-sparse set is precisely an independent set. A vector-weighted graph $ (G,\\vec{w},t)$ is a graph G with a vector weight function $ \\vec{w}:V(G)\\to {\\mathbb{R}}^{t+2}$, where $ \\vec{w}(v)=(w(v;-1),w(v;0),\\dots,w(v;t))$ for each v ∈ V ( G ). The weight of a t -sparse set S in $ (G,\\vec{w},t)$ is defined as $ \\vec{w}(S,G)={\\sum }_v w(v;{d}_S(G;v))$. And a t -sparse set S is a maximum weight t -sparse set of $ (G,\\vec{w},t)$ if there is no t -sparse set of larger weight in $ (G,\\vec{w},t)$. In this paper, we propose the maximum weight t -sparse set problem on vector-weighted graphs, which is to find a maximum weight t -sparse set of $ (G,\\vec{w},t)$. We design a dynamic programming algorithm to find a maximum weight t -sparse set of an outerplane graph $ (G,\\vec{w},t)$ which takes O (( t + 2) 4 n ) time, where n = | V ( G )|. Moreover, we give a polynomial-time algorithm for this problem on graphs with bounded treewidth.","PeriodicalId":54509,"journal":{"name":"Rairo-Operations Research","volume":"42 1","pages":"0"},"PeriodicalIF":1.8000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rairo-Operations Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1051/ro/2023145","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Let t be a nonnegative integer and G = ( V ( G ), E ( G )) be a graph. For v ∈ V ( G ), let N G ( v ) = { u ∈ V ( G ) \ { v } : uv ∈ E ( G )}. And for S ⊆ V ( G ), we define d S ( G ; v ) = | N G (v) ∩ S | for v ∈ S and d S ( G ; v ) = −1 for v ∈ V ( G ) \ S . A subset S ⊆ V ( G ) is called a t -sparse set of G if the maximum degree of the induced subgraph G [ S ] does not exceed t . In particular, a 0-sparse set is precisely an independent set. A vector-weighted graph $ (G,\vec{w},t)$ is a graph G with a vector weight function $ \vec{w}:V(G)\to {\mathbb{R}}^{t+2}$, where $ \vec{w}(v)=(w(v;-1),w(v;0),\dots,w(v;t))$ for each v ∈ V ( G ). The weight of a t -sparse set S in $ (G,\vec{w},t)$ is defined as $ \vec{w}(S,G)={\sum }_v w(v;{d}_S(G;v))$. And a t -sparse set S is a maximum weight t -sparse set of $ (G,\vec{w},t)$ if there is no t -sparse set of larger weight in $ (G,\vec{w},t)$. In this paper, we propose the maximum weight t -sparse set problem on vector-weighted graphs, which is to find a maximum weight t -sparse set of $ (G,\vec{w},t)$. We design a dynamic programming algorithm to find a maximum weight t -sparse set of an outerplane graph $ (G,\vec{w},t)$ which takes O (( t + 2) 4 n ) time, where n = | V ( G )|. Moreover, we give a polynomial-time algorithm for this problem on graphs with bounded treewidth.
期刊介绍:
RAIRO-Operations Research is an international journal devoted to high-level pure and applied research on all aspects of operations research. All papers published in RAIRO-Operations Research are critically refereed according to international standards. Any paper will either be accepted (possibly with minor revisions) either submitted to another evaluation (after a major revision) or rejected. Every effort will be made by the Editorial Board to ensure a first answer concerning a submitted paper within three months, and a final decision in a period of time not exceeding six months.