Application of continuous Hopfield network to solve the TSP
Traveling salesman problem (TSP) is a classic of difficult optimization problem. It is simple to describe, mathematically well characterized. But the actual best solution to TSP is computationally very hard, called a NP-complete problem. In this paper, continuous Hopfield network (CHN) is applied to...
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| creator | Helei Wu Yirong Yang |
| description | Traveling salesman problem (TSP) is a classic of difficult optimization problem. It is simple to describe, mathematically well characterized. But the actual best solution to TSP is computationally very hard, called a NP-complete problem. In this paper, continuous Hopfield network (CHN) is applied to solve TSP. The energy function to be minimized is determined both by constraints for a valid solution and by total length of touring path. Setting of parameters in energy function is crucial to the convergence and performance of the network. The role of each parameter is analyzed and criteria for choosing these parameters are described. Iterative computation algorithm of CHN is given. Computer simulation is conducted for 6-, City TSP. Some simulation results, such as convergence curve, iteration count, computation time, are used to evaluate this method. |
| doi_str_mv | 10.1109/ICARCV.2004.1469783 |
| format | Conference Proceeding |
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It is simple to describe, mathematically well characterized. But the actual best solution to TSP is computationally very hard, called a NP-complete problem. In this paper, continuous Hopfield network (CHN) is applied to solve TSP. The energy function to be minimized is determined both by constraints for a valid solution and by total length of touring path. Setting of parameters in energy function is crucial to the convergence and performance of the network. The role of each parameter is analyzed and criteria for choosing these parameters are described. Iterative computation algorithm of CHN is given. Computer simulation is conducted for 6-, City TSP. Some simulation results, such as convergence curve, iteration count, computation time, are used to evaluate this method.</description><identifier>ISBN: 9780780386532</identifier><identifier>ISBN: 0780386531</identifier><identifier>DOI: 10.1109/ICARCV.2004.1469783</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cities and towns ; Computational modeling ; Computer simulation ; Convergence ; Floods ; Iterative algorithms ; Mathematical model ; NP-complete problem ; Symmetric matrices ; Traveling salesman problems</subject><ispartof>ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004, 2004, Vol.3, p.2258-2263 Vol. 3</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1469783$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,4036,4037,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1469783$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Helei Wu</creatorcontrib><creatorcontrib>Yirong Yang</creatorcontrib><title>Application of continuous Hopfield network to solve the TSP</title><title>ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004</title><addtitle>ICARCV</addtitle><description>Traveling salesman problem (TSP) is a classic of difficult optimization problem. It is simple to describe, mathematically well characterized. But the actual best solution to TSP is computationally very hard, called a NP-complete problem. In this paper, continuous Hopfield network (CHN) is applied to solve TSP. The energy function to be minimized is determined both by constraints for a valid solution and by total length of touring path. Setting of parameters in energy function is crucial to the convergence and performance of the network. The role of each parameter is analyzed and criteria for choosing these parameters are described. Iterative computation algorithm of CHN is given. Computer simulation is conducted for 6-, City TSP. Some simulation results, such as convergence curve, iteration count, computation time, are used to evaluate this method.</description><subject>Cities and towns</subject><subject>Computational modeling</subject><subject>Computer simulation</subject><subject>Convergence</subject><subject>Floods</subject><subject>Iterative algorithms</subject><subject>Mathematical model</subject><subject>NP-complete problem</subject><subject>Symmetric matrices</subject><subject>Traveling salesman problems</subject><isbn>9780780386532</isbn><isbn>0780386531</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9jkELgjAYQAcRFOUv8PL9geybU5t0EinsFiVdRWzSyrbhZtG_z0Pn4ME7vMsjxKcYUIrp-pBnp_wShIhRQKMk3XA2Id4oHGE8iVk4I561d0SkacJ5TOdkmxnTyaZ2UivQLTRaOakGPVgotGml6K6ghHvr_gFOg9XdS4C7CSjPxyWZtnVnhffzgvj7XZkXKymEqEwvn3X_qX4r7H_9AnwAODg</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Helei Wu</creator><creator>Yirong Yang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2004</creationdate><title>Application of continuous Hopfield network to solve the TSP</title><author>Helei Wu ; Yirong Yang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_14697833</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Cities and towns</topic><topic>Computational modeling</topic><topic>Computer simulation</topic><topic>Convergence</topic><topic>Floods</topic><topic>Iterative algorithms</topic><topic>Mathematical model</topic><topic>NP-complete problem</topic><topic>Symmetric matrices</topic><topic>Traveling salesman problems</topic><toplevel>online_resources</toplevel><creatorcontrib>Helei Wu</creatorcontrib><creatorcontrib>Yirong Yang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Helei Wu</au><au>Yirong Yang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Application of continuous Hopfield network to solve the TSP</atitle><btitle>ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004</btitle><stitle>ICARCV</stitle><date>2004</date><risdate>2004</risdate><volume>3</volume><spage>2258</spage><epage>2263 Vol. 3</epage><pages>2258-2263 Vol. 3</pages><isbn>9780780386532</isbn><isbn>0780386531</isbn><abstract>Traveling salesman problem (TSP) is a classic of difficult optimization problem. It is simple to describe, mathematically well characterized. But the actual best solution to TSP is computationally very hard, called a NP-complete problem. In this paper, continuous Hopfield network (CHN) is applied to solve TSP. The energy function to be minimized is determined both by constraints for a valid solution and by total length of touring path. Setting of parameters in energy function is crucial to the convergence and performance of the network. The role of each parameter is analyzed and criteria for choosing these parameters are described. Iterative computation algorithm of CHN is given. Computer simulation is conducted for 6-, City TSP. Some simulation results, such as convergence curve, iteration count, computation time, are used to evaluate this method.</abstract><pub>IEEE</pub><doi>10.1109/ICARCV.2004.1469783</doi></addata></record> |
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| identifier | ISBN: 9780780386532 |
| ispartof | ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004, 2004, Vol.3, p.2258-2263 Vol. 3 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Cities and towns Computational modeling Computer simulation Convergence Floods Iterative algorithms Mathematical model NP-complete problem Symmetric matrices Traveling salesman problems |
| title | Application of continuous Hopfield network to solve the TSP |
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