CSpace  > 应用数学研究所
 Risk Models for the Prize Collecting Steiner Tree Problems with Interval Data Alternative Title Risk Models for the Prize Collecting Steiner Tree Problems with Interval Data AlvarezMiranda Eduardo1; CandiaVejar Alfredo1; Chen Xujin3; Hu Xiaodong3; Li Bi3 2014 Source Publication ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES ISSN 0168-9673 Volume 30Issue:1Pages:1-26 Abstract Given a connected graph G = (V, E) with a nonnegative cost on each edge in E, a nonnegative prize at each vertex in V, and a target set V-1 subset of V, the Prize Collecting Steiner Tree (POST) problem is to find a tree T in G interconnecting all vertices of V-1 such that the total cost on edges in T minus the total prize at vertices in T is minimized. The PCST problem appears frequently in practice of operations research. While the problem is NP-hard in general, it is polynomial-time solvable when graphs G are restricted to series-parallel graphs. Other Abstract Given a connected graph G=(V,E)with a nonnegative cost on each edge in E,a nonnegative prize at each vertex in V,and a target set V′?V,the Prize Collecting Steiner Tree(PCST)problem is to find a tree T in G interconnecting all vertices of V′such that the total cost on edges in T minus the total prize at vertices in T is minimized.The PCST problem appears frequently in practice of operations research.While the problem is NP-hard in general,it is polynomial-time solvable when graphs G are restricted to series-parallel graphs.In this paper,we study the PCST problem with interval costs and prizes,where edge e could be included in T by paying cost x_e∈c_e~-,c_e~+while taking risk(c_e~+ x_e)/(c_e~+ c_e)of malfunction at e,and vertex v could be asked for giving a prize y_v∈p_v~-,p_v~+for its inclusion in T while taking risk(y_v -p_v~-)/(p_v~+ p_v~-)of refusal by v.We establish two risk models for the PCST problem with interval data.Under given budget upper bound on constructing tree T,one model aims at minimizing the maximum risk over edges and vertices in T and the other aims at minimizing the sum of risks over edges and vertices in T.We propose strongly polynomial-time algorithms solving these problems on series-parallel graphs to optimality.Our study shows that the risk models proposed have advantages over the existing robust optimization model,which often yields NP-hard problems even if the original optimization problems are polynomial-time solvable. Keyword SERIES-PARALLEL GRAPHS SHORTEST-PATH PROBLEM COMPUTATIONAL-COMPLEXITY NETWORK OPTIMIZATION CONSTRAINTS ALGORITHMS FLOWS uncertainty modeling prize collecting Steiner tree interval data series-parallel graphs polynomial-time solvability Indexed By CSCD Language 英语 Funding Project [National Natural Science Foundation of China] ; [973 Program of China] ; [Chinese Academy of Sciences] ; [Center for Research and Applications in Plasma Physics and Pulsed Power Technology, PBCT-Chile-ACT 26] ; [Direccion de Programas de Investigacion, Universidad de Talca, Chile] CSCD ID CSCD:5097895 Citation statistics Document Type 期刊论文 Identifier http://ir.amss.ac.cn/handle/2S8OKBNM/53487 Collection 应用数学研究所 Affiliation 1.University Talca, Ind Management Dept, Talca, Chile2.University Bologna, DEI, I-40126 Bologna, Italy3.中国科学院数学与系统科学研究院 Recommended CitationGB/T 7714 AlvarezMiranda Eduardo,CandiaVejar Alfredo,Chen Xujin,et al. Risk Models for the Prize Collecting Steiner Tree Problems with Interval Data[J]. ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES,2014,30(1):1-26. APA AlvarezMiranda Eduardo,CandiaVejar Alfredo,Chen Xujin,Hu Xiaodong,&Li Bi.(2014).Risk Models for the Prize Collecting Steiner Tree Problems with Interval Data.ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES,30(1),1-26. MLA AlvarezMiranda Eduardo,et al."Risk Models for the Prize Collecting Steiner Tree Problems with Interval Data".ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES 30.1(2014):1-26.
 Files in This Item: There are no files associated with this item.
 Related Services Recommend this item Bookmark Usage statistics Export to Endnote Google Scholar Similar articles in Google Scholar [AlvarezMiranda Eduardo]'s Articles [CandiaVejar Alfredo]'s Articles [Chen Xujin]'s Articles Baidu academic Similar articles in Baidu academic [AlvarezMiranda Eduardo]'s Articles [CandiaVejar Alfredo]'s Articles [Chen Xujin]'s Articles Bing Scholar Similar articles in Bing Scholar [AlvarezMiranda Eduardo]'s Articles [CandiaVejar Alfredo]'s Articles [Chen Xujin]'s Articles Terms of Use No data! Social Bookmark/Share
No comment.