Computing the Minimum Cost Pipe Network Interconnecting One Sink and Many Sources
In this paper, we study the problem of computing the minimum cost pipe network interconnecting a given set of wells and a treatment site, where each well has a given capacity and the treatment site has a capacity that is no less than the sum of all the capacities of the wells. This is a generalized...
Gespeichert in:
Veröffentlicht in: | SIAM journal on optimization 1999, Vol.10 (1), p.22-42 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 42 |
---|---|
container_issue | 1 |
container_start_page | 22 |
container_title | SIAM journal on optimization |
container_volume | 10 |
creator | Xue, Guoliang Lillys, Theodore P. Dougherty, David E. |
description | In this paper, we study the problem of computing the minimum cost pipe network interconnecting a given set of wells and a treatment site, where each well has a given capacity and the treatment site has a capacity that is no less than the sum of all the capacities of the wells. This is a generalized Steiner minimum tree problem which has applications in communication networks and in groundwater treatment. We prove that there exists a minimum cost pipe network that is the minimum cost network under a full Steiner topology. For each given full Steiner topology, we can compute all the edge weights in linear time. A powerful interior-point algorithm is then used to find the minimum cost network under this given topology. We also prove a lower bound theorem which enables pruning in a backtrack method that partially enumerates the full Steiner topologies in search for a minimum cost pipe network. A heuristic ordering algorithm is proposed to enhance the performance of the backtrack algorithm. We then define the notion of k-optimality and present an efficient (polynomial time) algorithm for checking 5-optimality. We present a 5-optimal heuristic algorithm for computing good solutions when the problem size is too large for the exact algorithm. Computational results are presented. |
doi_str_mv | 10.1137/S1052623496313684 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_920816316</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2582693861</sourcerecordid><originalsourceid>FETCH-LOGICAL-c270t-8f0211b020e0ae6293191c53323f52c583454a63334844a530d728389ad8b2ca3</originalsourceid><addsrcrecordid>eNplkMtOwzAQRS0EEqXwAews9gHbYzv2EkU8KrUUFFhHrutAWmIHOxHq35NSdqxmpDmae3UQuqTkmlLIb0pKBJMMuJZAQSp-hCaUaJHlVOnj_S5Ytr-forOUNoQQpaWaoJcitN3QN_4d9x8OLxrftEOLi5B6_Nx0Dj-5_jvELZ753kUbvHf2l156h8vGb7Hxa7wwfofLMETr0jk6qc1nchd_c4re7u9ei8dsvnyYFbfzzLKc9JmqCaN0RRhxxDjJNFBNrQBgUAtmhQIuuJEAwBXnRgBZ50yB0matVswamKKrw98uhq_Bpb7ajAX8GFlpRhQdPcgRogfIxpBSdHXVxaY1cVdRUu3FVf_EwQ_8Dl4c</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>920816316</pqid></control><display><type>article</type><title>Computing the Minimum Cost Pipe Network Interconnecting One Sink and Many Sources</title><source>SIAM Journals Online</source><creator>Xue, Guoliang ; Lillys, Theodore P. ; Dougherty, David E.</creator><creatorcontrib>Xue, Guoliang ; Lillys, Theodore P. ; Dougherty, David E.</creatorcontrib><description>In this paper, we study the problem of computing the minimum cost pipe network interconnecting a given set of wells and a treatment site, where each well has a given capacity and the treatment site has a capacity that is no less than the sum of all the capacities of the wells. This is a generalized Steiner minimum tree problem which has applications in communication networks and in groundwater treatment. We prove that there exists a minimum cost pipe network that is the minimum cost network under a full Steiner topology. For each given full Steiner topology, we can compute all the edge weights in linear time. A powerful interior-point algorithm is then used to find the minimum cost network under this given topology. We also prove a lower bound theorem which enables pruning in a backtrack method that partially enumerates the full Steiner topologies in search for a minimum cost pipe network. A heuristic ordering algorithm is proposed to enhance the performance of the backtrack algorithm. We then define the notion of k-optimality and present an efficient (polynomial time) algorithm for checking 5-optimality. We present a 5-optimal heuristic algorithm for computing good solutions when the problem size is too large for the exact algorithm. Computational results are presented.</description><identifier>ISSN: 1052-6234</identifier><identifier>EISSN: 1095-7189</identifier><identifier>DOI: 10.1137/S1052623496313684</identifier><language>eng</language><publisher>Philadelphia: Society for Industrial and Applied Mathematics</publisher><subject>Algorithms ; Applied mathematics ; Communication ; Communications networks ; Environmental engineering ; Grants ; Groundwater ; Heuristic ; Mathematical models</subject><ispartof>SIAM journal on optimization, 1999, Vol.10 (1), p.22-42</ispartof><rights>[Copyright] © 1999 Society for Industrial and Applied Mathematics</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c270t-8f0211b020e0ae6293191c53323f52c583454a63334844a530d728389ad8b2ca3</citedby><cites>FETCH-LOGICAL-c270t-8f0211b020e0ae6293191c53323f52c583454a63334844a530d728389ad8b2ca3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,3182,4021,27921,27922,27923</link.rule.ids></links><search><creatorcontrib>Xue, Guoliang</creatorcontrib><creatorcontrib>Lillys, Theodore P.</creatorcontrib><creatorcontrib>Dougherty, David E.</creatorcontrib><title>Computing the Minimum Cost Pipe Network Interconnecting One Sink and Many Sources</title><title>SIAM journal on optimization</title><description>In this paper, we study the problem of computing the minimum cost pipe network interconnecting a given set of wells and a treatment site, where each well has a given capacity and the treatment site has a capacity that is no less than the sum of all the capacities of the wells. This is a generalized Steiner minimum tree problem which has applications in communication networks and in groundwater treatment. We prove that there exists a minimum cost pipe network that is the minimum cost network under a full Steiner topology. For each given full Steiner topology, we can compute all the edge weights in linear time. A powerful interior-point algorithm is then used to find the minimum cost network under this given topology. We also prove a lower bound theorem which enables pruning in a backtrack method that partially enumerates the full Steiner topologies in search for a minimum cost pipe network. A heuristic ordering algorithm is proposed to enhance the performance of the backtrack algorithm. We then define the notion of k-optimality and present an efficient (polynomial time) algorithm for checking 5-optimality. We present a 5-optimal heuristic algorithm for computing good solutions when the problem size is too large for the exact algorithm. Computational results are presented.</description><subject>Algorithms</subject><subject>Applied mathematics</subject><subject>Communication</subject><subject>Communications networks</subject><subject>Environmental engineering</subject><subject>Grants</subject><subject>Groundwater</subject><subject>Heuristic</subject><subject>Mathematical models</subject><issn>1052-6234</issn><issn>1095-7189</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1999</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNplkMtOwzAQRS0EEqXwAews9gHbYzv2EkU8KrUUFFhHrutAWmIHOxHq35NSdqxmpDmae3UQuqTkmlLIb0pKBJMMuJZAQSp-hCaUaJHlVOnj_S5Ytr-forOUNoQQpaWaoJcitN3QN_4d9x8OLxrftEOLi5B6_Nx0Dj-5_jvELZ753kUbvHf2l156h8vGb7Hxa7wwfofLMETr0jk6qc1nchd_c4re7u9ei8dsvnyYFbfzzLKc9JmqCaN0RRhxxDjJNFBNrQBgUAtmhQIuuJEAwBXnRgBZ50yB0matVswamKKrw98uhq_Bpb7ajAX8GFlpRhQdPcgRogfIxpBSdHXVxaY1cVdRUu3FVf_EwQ_8Dl4c</recordid><startdate>1999</startdate><enddate>1999</enddate><creator>Xue, Guoliang</creator><creator>Lillys, Theodore P.</creator><creator>Dougherty, David E.</creator><general>Society for Industrial and Applied Mathematics</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RQ</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X2</scope><scope>7XB</scope><scope>87Z</scope><scope>88A</scope><scope>88F</scope><scope>88I</scope><scope>88K</scope><scope>8AL</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>KB.</scope><scope>L.-</scope><scope>L6V</scope><scope>LK8</scope><scope>M0C</scope><scope>M0K</scope><scope>M0N</scope><scope>M1Q</scope><scope>M2O</scope><scope>M2P</scope><scope>M2T</scope><scope>M7P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>U9A</scope></search><sort><creationdate>1999</creationdate><title>Computing the Minimum Cost Pipe Network Interconnecting One Sink and Many Sources</title><author>Xue, Guoliang ; Lillys, Theodore P. ; Dougherty, David E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c270t-8f0211b020e0ae6293191c53323f52c583454a63334844a530d728389ad8b2ca3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Algorithms</topic><topic>Applied mathematics</topic><topic>Communication</topic><topic>Communications networks</topic><topic>Environmental engineering</topic><topic>Grants</topic><topic>Groundwater</topic><topic>Heuristic</topic><topic>Mathematical models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xue, Guoliang</creatorcontrib><creatorcontrib>Lillys, Theodore P.</creatorcontrib><creatorcontrib>Dougherty, David E.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Career & Technical Education Database</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Military Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Telecommunications (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>Materials Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>ABI/INFORM Global</collection><collection>Agricultural Science Database</collection><collection>Computing Database</collection><collection>Military Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Telecommunications Database</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><jtitle>SIAM journal on optimization</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xue, Guoliang</au><au>Lillys, Theodore P.</au><au>Dougherty, David E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computing the Minimum Cost Pipe Network Interconnecting One Sink and Many Sources</atitle><jtitle>SIAM journal on optimization</jtitle><date>1999</date><risdate>1999</risdate><volume>10</volume><issue>1</issue><spage>22</spage><epage>42</epage><pages>22-42</pages><issn>1052-6234</issn><eissn>1095-7189</eissn><abstract>In this paper, we study the problem of computing the minimum cost pipe network interconnecting a given set of wells and a treatment site, where each well has a given capacity and the treatment site has a capacity that is no less than the sum of all the capacities of the wells. This is a generalized Steiner minimum tree problem which has applications in communication networks and in groundwater treatment. We prove that there exists a minimum cost pipe network that is the minimum cost network under a full Steiner topology. For each given full Steiner topology, we can compute all the edge weights in linear time. A powerful interior-point algorithm is then used to find the minimum cost network under this given topology. We also prove a lower bound theorem which enables pruning in a backtrack method that partially enumerates the full Steiner topologies in search for a minimum cost pipe network. A heuristic ordering algorithm is proposed to enhance the performance of the backtrack algorithm. We then define the notion of k-optimality and present an efficient (polynomial time) algorithm for checking 5-optimality. We present a 5-optimal heuristic algorithm for computing good solutions when the problem size is too large for the exact algorithm. Computational results are presented.</abstract><cop>Philadelphia</cop><pub>Society for Industrial and Applied Mathematics</pub><doi>10.1137/S1052623496313684</doi><tpages>21</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1052-6234 |
ispartof | SIAM journal on optimization, 1999, Vol.10 (1), p.22-42 |
issn | 1052-6234 1095-7189 |
language | eng |
recordid | cdi_proquest_journals_920816316 |
source | SIAM Journals Online |
subjects | Algorithms Applied mathematics Communication Communications networks Environmental engineering Grants Groundwater Heuristic Mathematical models |
title | Computing the Minimum Cost Pipe Network Interconnecting One Sink and Many Sources |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T12%3A21%3A33IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Computing%20the%20Minimum%20Cost%20Pipe%20Network%20Interconnecting%20One%20Sink%20and%20Many%20Sources&rft.jtitle=SIAM%20journal%20on%20optimization&rft.au=Xue,%20Guoliang&rft.date=1999&rft.volume=10&rft.issue=1&rft.spage=22&rft.epage=42&rft.pages=22-42&rft.issn=1052-6234&rft.eissn=1095-7189&rft_id=info:doi/10.1137/S1052623496313684&rft_dat=%3Cproquest_cross%3E2582693861%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=920816316&rft_id=info:pmid/&rfr_iscdi=true |