The multi-terminal maximum-flow network-interdiction problem
This paper defines and studies the multi-terminal maximum-flow network-interdiction problem (MTNIP) in which a network user attempts to maximize flow in a network among K ⩾ 3 pre-specified node groups while an interdictor uses limited resources to interdict network arcs to minimize this maximum flow...
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Veröffentlicht in: | European journal of operational research 2011-06, Vol.211 (2), p.241-251 |
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creator | Akgün, İbrahim Tansel, Barbaros Ç. Kevin Wood, R. |
description | This paper defines and studies the multi-terminal maximum-flow network-interdiction problem (MTNIP) in which a
network user attempts to maximize flow in a network among
K
⩾
3 pre-specified
node groups while an
interdictor uses limited resources to interdict network arcs to minimize this maximum flow. The paper proposes an exact (MTNIP-E) and an approximating model (MPNIM) to solve this NP-hard problem and presents computational results to compare the models. MTNIP-E is obtained by first formulating MTNIP as bi-level min–max program and then converting it into a mixed integer program where the flow is explicitly minimized. MPNIM is binary-integer program that does not minimize the flow directly. It partitions the node set into disjoint subsets such that each node group is in a different subset and minimizes the sum of the arc capacities crossing between different subsets. Computational results show that MPNIM can solve all instances in a few seconds while MTNIP-E cannot solve about one third of the problems in 24
hour. The optimal objective function values of both models are equal to each other for some problems while they differ from each other as much as 46.2% in the worst case. However, when the post-interdiction flow capacity incurred by the solution of MPNIM is computed and compared to the objective value of MTNIP-E, the largest difference is only 7.90% implying that MPNIM may be a very good approximation to MTNIP-E. |
doi_str_mv | 10.1016/j.ejor.2010.12.011 |
format | Article |
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network user attempts to maximize flow in a network among
K
⩾
3 pre-specified
node groups while an
interdictor uses limited resources to interdict network arcs to minimize this maximum flow. The paper proposes an exact (MTNIP-E) and an approximating model (MPNIM) to solve this NP-hard problem and presents computational results to compare the models. MTNIP-E is obtained by first formulating MTNIP as bi-level min–max program and then converting it into a mixed integer program where the flow is explicitly minimized. MPNIM is binary-integer program that does not minimize the flow directly. It partitions the node set into disjoint subsets such that each node group is in a different subset and minimizes the sum of the arc capacities crossing between different subsets. Computational results show that MPNIM can solve all instances in a few seconds while MTNIP-E cannot solve about one third of the problems in 24
hour. The optimal objective function values of both models are equal to each other for some problems while they differ from each other as much as 46.2% in the worst case. However, when the post-interdiction flow capacity incurred by the solution of MPNIM is computed and compared to the objective value of MTNIP-E, the largest difference is only 7.90% implying that MPNIM may be a very good approximation to MTNIP-E.</description><identifier>ISSN: 0377-2217</identifier><identifier>EISSN: 1872-6860</identifier><identifier>DOI: 10.1016/j.ejor.2010.12.011</identifier><identifier>CODEN: EJORDT</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Applied sciences ; Approximation ; Computation ; Exact sciences and technology ; Flows in networks. Combinatorial problems ; Integer programming ; Mathematical analysis ; Mathematical models ; Mathematical programming ; Mixed integer ; Network flow problem ; Network flows ; Network interdiction ; Networks ; Operational research and scientific management ; Operational research. Management science ; Optimization ; Optimization algorithms ; OR in military ; OR in military Integer programming Network flows Network interdiction ; Studies</subject><ispartof>European journal of operational research, 2011-06, Vol.211 (2), p.241-251</ispartof><rights>2010 Elsevier B.V.</rights><rights>2015 INIST-CNRS</rights><rights>Copyright Elsevier Sequoia S.A. Jun 1, 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c598t-78e3b1e690f914f966c6448c0e4bd8079953462fb1fa1351a0c186326345ffd73</citedby><cites>FETCH-LOGICAL-c598t-78e3b1e690f914f966c6448c0e4bd8079953462fb1fa1351a0c186326345ffd73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ejor.2010.12.011$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,4006,27923,27924,45994</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23897473$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttp://econpapers.repec.org/article/eeeejores/v_3a211_3ay_3a2011_3ai_3a2_3ap_3a241-251.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Akgün, İbrahim</creatorcontrib><creatorcontrib>Tansel, Barbaros Ç.</creatorcontrib><creatorcontrib>Kevin Wood, R.</creatorcontrib><title>The multi-terminal maximum-flow network-interdiction problem</title><title>European journal of operational research</title><description>This paper defines and studies the multi-terminal maximum-flow network-interdiction problem (MTNIP) in which a
network user attempts to maximize flow in a network among
K
⩾
3 pre-specified
node groups while an
interdictor uses limited resources to interdict network arcs to minimize this maximum flow. The paper proposes an exact (MTNIP-E) and an approximating model (MPNIM) to solve this NP-hard problem and presents computational results to compare the models. MTNIP-E is obtained by first formulating MTNIP as bi-level min–max program and then converting it into a mixed integer program where the flow is explicitly minimized. MPNIM is binary-integer program that does not minimize the flow directly. It partitions the node set into disjoint subsets such that each node group is in a different subset and minimizes the sum of the arc capacities crossing between different subsets. Computational results show that MPNIM can solve all instances in a few seconds while MTNIP-E cannot solve about one third of the problems in 24
hour. The optimal objective function values of both models are equal to each other for some problems while they differ from each other as much as 46.2% in the worst case. However, when the post-interdiction flow capacity incurred by the solution of MPNIM is computed and compared to the objective value of MTNIP-E, the largest difference is only 7.90% implying that MPNIM may be a very good approximation to MTNIP-E.</description><subject>Applied sciences</subject><subject>Approximation</subject><subject>Computation</subject><subject>Exact sciences and technology</subject><subject>Flows in networks. Combinatorial problems</subject><subject>Integer programming</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Mathematical programming</subject><subject>Mixed integer</subject><subject>Network flow problem</subject><subject>Network flows</subject><subject>Network interdiction</subject><subject>Networks</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Optimization</subject><subject>Optimization algorithms</subject><subject>OR in military</subject><subject>OR in military Integer programming Network flows Network interdiction</subject><subject>Studies</subject><issn>0377-2217</issn><issn>1872-6860</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNp9kE1v1DAQhi0EEkvLH-C0QkKcsnj8HakXVNEWUamXcra8zlh1iJPFTlr673G6VQ8csGTPyH7mnfFLyAegO6CgvvQ77Ke8Y3S9YDsK8IpswGjWKKPoa7KhXOuGMdBvybtSekopSJAbcnZ7h9u0DHNsZswpjm7YJvcnpiU1YZgetiPOD1P-1cSxvnfRz3Eat4c87QdMp-RNcEPB98_xhPy8-HZ7ftVc31x-P_963XjZmrnRBvkeULU0tCBCq5RXQhhPUew7Q3XbSi4UC3sIDrgERz0YxZniQobQaX5CPh91a9_fC5bZplg8DoMbcVqKNVUOBFdQyY__kP205PqpCkmmpGyZrBA7Qj5PpWQM9pBjcvnRArWrnba3q512tdMCs9XOWvTjWJTxgP6lAuuqKBZ7b7ljAPV8XDP6lMY1rfuwRgGWSbB3c6pqn57ndMW7IWQ3-lheVBk3rRaaV-7syGG19z5itsVHHD12MaOfbTfF_w39FyekouQ</recordid><startdate>20110601</startdate><enddate>20110601</enddate><creator>Akgün, İbrahim</creator><creator>Tansel, Barbaros Ç.</creator><creator>Kevin Wood, R.</creator><general>Elsevier B.V</general><general>Elsevier</general><general>Elsevier Sequoia S.A</general><scope>IQODW</scope><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7TA</scope><scope>JG9</scope></search><sort><creationdate>20110601</creationdate><title>The multi-terminal maximum-flow network-interdiction problem</title><author>Akgün, İbrahim ; Tansel, Barbaros Ç. ; Kevin Wood, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c598t-78e3b1e690f914f966c6448c0e4bd8079953462fb1fa1351a0c186326345ffd73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Applied sciences</topic><topic>Approximation</topic><topic>Computation</topic><topic>Exact sciences and technology</topic><topic>Flows in networks. Combinatorial problems</topic><topic>Integer programming</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Mathematical programming</topic><topic>Mixed integer</topic><topic>Network flow problem</topic><topic>Network flows</topic><topic>Network interdiction</topic><topic>Networks</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>Optimization</topic><topic>Optimization algorithms</topic><topic>OR in military</topic><topic>OR in military Integer programming Network flows Network interdiction</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Akgün, İbrahim</creatorcontrib><creatorcontrib>Tansel, Barbaros Ç.</creatorcontrib><creatorcontrib>Kevin Wood, R.</creatorcontrib><collection>Pascal-Francis</collection><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Materials Business File</collection><collection>Materials Research Database</collection><jtitle>European journal of operational research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Akgün, İbrahim</au><au>Tansel, Barbaros Ç.</au><au>Kevin Wood, R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The multi-terminal maximum-flow network-interdiction problem</atitle><jtitle>European journal of operational research</jtitle><date>2011-06-01</date><risdate>2011</risdate><volume>211</volume><issue>2</issue><spage>241</spage><epage>251</epage><pages>241-251</pages><issn>0377-2217</issn><eissn>1872-6860</eissn><coden>EJORDT</coden><abstract>This paper defines and studies the multi-terminal maximum-flow network-interdiction problem (MTNIP) in which a
network user attempts to maximize flow in a network among
K
⩾
3 pre-specified
node groups while an
interdictor uses limited resources to interdict network arcs to minimize this maximum flow. The paper proposes an exact (MTNIP-E) and an approximating model (MPNIM) to solve this NP-hard problem and presents computational results to compare the models. MTNIP-E is obtained by first formulating MTNIP as bi-level min–max program and then converting it into a mixed integer program where the flow is explicitly minimized. MPNIM is binary-integer program that does not minimize the flow directly. It partitions the node set into disjoint subsets such that each node group is in a different subset and minimizes the sum of the arc capacities crossing between different subsets. Computational results show that MPNIM can solve all instances in a few seconds while MTNIP-E cannot solve about one third of the problems in 24
hour. The optimal objective function values of both models are equal to each other for some problems while they differ from each other as much as 46.2% in the worst case. However, when the post-interdiction flow capacity incurred by the solution of MPNIM is computed and compared to the objective value of MTNIP-E, the largest difference is only 7.90% implying that MPNIM may be a very good approximation to MTNIP-E.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.ejor.2010.12.011</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Applied sciences Approximation Computation Exact sciences and technology Flows in networks. Combinatorial problems Integer programming Mathematical analysis Mathematical models Mathematical programming Mixed integer Network flow problem Network flows Network interdiction Networks Operational research and scientific management Operational research. Management science Optimization Optimization algorithms OR in military OR in military Integer programming Network flows Network interdiction Studies |
title | The multi-terminal maximum-flow network-interdiction problem |
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