A general variable neighborhood search approach for the minimum load coloring problem

Abstract The minimum load coloring problem consists of finding a 2-coloring function that assign either a color red or blue to each node of a graph such that the (maximum) load is minimized, i.e., to reduce as much as possible the number of edges with, at least, one endpoint colored in red (symmetri...
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Gespeichert in:

Autor*in:	Herrán, Alberto [verfasserIn] Colmenar, J. Manuel Mladenović, Nenad Duarte, Abraham

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Metaheuristics Variable neighborhood search Graph coloring problem Graph partition problem

Anmerkung:	© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022

Übergeordnetes Werk:	Enthalten in: Optimization letters - Berlin : Springer, 2007, 17(2022), 9 vom: 03. März, Seite 2065-2086
Übergeordnetes Werk:	volume:17 ; year:2022 ; number:9 ; day:03 ; month:03 ; pages:2065-2086

Links:	Volltext

DOI / URN:	10.1007/s11590-022-01861-1

Katalog-ID:	SPR053575415

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allfields	10.1007/s11590-022-01861-1 doi (DE-627)SPR053575415 (SPR)s11590-022-01861-1-e DE-627 ger DE-627 rakwb eng Herrán, Alberto verfasserin aut A general variable neighborhood search approach for the minimum load coloring problem 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract The minimum load coloring problem consists of finding a 2-coloring function that assign either a color red or blue to each node of a graph such that the (maximum) load is minimized, i.e., to reduce as much as possible the number of edges with, at least, one endpoint colored in red (symmetrically, in blue). This %$\mathcal {NP}%$-complete problem arises in Wavelength Division Multiplexing (WDM) technology and it has been used for broadcast WDM networks. In this paper, several procedures based on the Variable Neighborhood Search (VNS) methodology are proposed and compared on a set of random graphs and DIMACS benchmarks. Experimental results show that the proposed VNS variant exhibits a remarkable performance in comparison with the state-of-the-art methods. In particular, our approach achieves the best results in 48 out of 52 considered instances by employing, on average, less than 7 seconds. These results are further confirmed by conducting statistical tests. Metaheuristics (dpeaa)DE-He213 Variable neighborhood search (dpeaa)DE-He213 Graph coloring problem (dpeaa)DE-He213 Graph partition problem (dpeaa)DE-He213 Colmenar, J. Manuel (orcid)0000-0001-7490-9450 aut Mladenović, Nenad aut Duarte, Abraham aut Enthalten in Optimization letters Berlin : Springer, 2007 17(2022), 9 vom: 03. März, Seite 2065-2086 (DE-627)534676499 (DE-600)2374345-1 1862-4480 nnns volume:17 year:2022 number:9 day:03 month:03 pages:2065-2086 https://dx.doi.org/10.1007/s11590-022-01861-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 17 2022 9 03 03 2065-2086
spelling	10.1007/s11590-022-01861-1 doi (DE-627)SPR053575415 (SPR)s11590-022-01861-1-e DE-627 ger DE-627 rakwb eng Herrán, Alberto verfasserin aut A general variable neighborhood search approach for the minimum load coloring problem 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract The minimum load coloring problem consists of finding a 2-coloring function that assign either a color red or blue to each node of a graph such that the (maximum) load is minimized, i.e., to reduce as much as possible the number of edges with, at least, one endpoint colored in red (symmetrically, in blue). This %$\mathcal {NP}%$-complete problem arises in Wavelength Division Multiplexing (WDM) technology and it has been used for broadcast WDM networks. In this paper, several procedures based on the Variable Neighborhood Search (VNS) methodology are proposed and compared on a set of random graphs and DIMACS benchmarks. Experimental results show that the proposed VNS variant exhibits a remarkable performance in comparison with the state-of-the-art methods. In particular, our approach achieves the best results in 48 out of 52 considered instances by employing, on average, less than 7 seconds. These results are further confirmed by conducting statistical tests. Metaheuristics (dpeaa)DE-He213 Variable neighborhood search (dpeaa)DE-He213 Graph coloring problem (dpeaa)DE-He213 Graph partition problem (dpeaa)DE-He213 Colmenar, J. Manuel (orcid)0000-0001-7490-9450 aut Mladenović, Nenad aut Duarte, Abraham aut Enthalten in Optimization letters Berlin : Springer, 2007 17(2022), 9 vom: 03. März, Seite 2065-2086 (DE-627)534676499 (DE-600)2374345-1 1862-4480 nnns volume:17 year:2022 number:9 day:03 month:03 pages:2065-2086 https://dx.doi.org/10.1007/s11590-022-01861-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 17 2022 9 03 03 2065-2086
allfields_unstemmed	10.1007/s11590-022-01861-1 doi (DE-627)SPR053575415 (SPR)s11590-022-01861-1-e DE-627 ger DE-627 rakwb eng Herrán, Alberto verfasserin aut A general variable neighborhood search approach for the minimum load coloring problem 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract The minimum load coloring problem consists of finding a 2-coloring function that assign either a color red or blue to each node of a graph such that the (maximum) load is minimized, i.e., to reduce as much as possible the number of edges with, at least, one endpoint colored in red (symmetrically, in blue). This %$\mathcal {NP}%$-complete problem arises in Wavelength Division Multiplexing (WDM) technology and it has been used for broadcast WDM networks. In this paper, several procedures based on the Variable Neighborhood Search (VNS) methodology are proposed and compared on a set of random graphs and DIMACS benchmarks. Experimental results show that the proposed VNS variant exhibits a remarkable performance in comparison with the state-of-the-art methods. In particular, our approach achieves the best results in 48 out of 52 considered instances by employing, on average, less than 7 seconds. These results are further confirmed by conducting statistical tests. Metaheuristics (dpeaa)DE-He213 Variable neighborhood search (dpeaa)DE-He213 Graph coloring problem (dpeaa)DE-He213 Graph partition problem (dpeaa)DE-He213 Colmenar, J. Manuel (orcid)0000-0001-7490-9450 aut Mladenović, Nenad aut Duarte, Abraham aut Enthalten in Optimization letters Berlin : Springer, 2007 17(2022), 9 vom: 03. März, Seite 2065-2086 (DE-627)534676499 (DE-600)2374345-1 1862-4480 nnns volume:17 year:2022 number:9 day:03 month:03 pages:2065-2086 https://dx.doi.org/10.1007/s11590-022-01861-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 17 2022 9 03 03 2065-2086
allfieldsGer	10.1007/s11590-022-01861-1 doi (DE-627)SPR053575415 (SPR)s11590-022-01861-1-e DE-627 ger DE-627 rakwb eng Herrán, Alberto verfasserin aut A general variable neighborhood search approach for the minimum load coloring problem 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract The minimum load coloring problem consists of finding a 2-coloring function that assign either a color red or blue to each node of a graph such that the (maximum) load is minimized, i.e., to reduce as much as possible the number of edges with, at least, one endpoint colored in red (symmetrically, in blue). This %$\mathcal {NP}%$-complete problem arises in Wavelength Division Multiplexing (WDM) technology and it has been used for broadcast WDM networks. In this paper, several procedures based on the Variable Neighborhood Search (VNS) methodology are proposed and compared on a set of random graphs and DIMACS benchmarks. Experimental results show that the proposed VNS variant exhibits a remarkable performance in comparison with the state-of-the-art methods. In particular, our approach achieves the best results in 48 out of 52 considered instances by employing, on average, less than 7 seconds. These results are further confirmed by conducting statistical tests. Metaheuristics (dpeaa)DE-He213 Variable neighborhood search (dpeaa)DE-He213 Graph coloring problem (dpeaa)DE-He213 Graph partition problem (dpeaa)DE-He213 Colmenar, J. Manuel (orcid)0000-0001-7490-9450 aut Mladenović, Nenad aut Duarte, Abraham aut Enthalten in Optimization letters Berlin : Springer, 2007 17(2022), 9 vom: 03. März, Seite 2065-2086 (DE-627)534676499 (DE-600)2374345-1 1862-4480 nnns volume:17 year:2022 number:9 day:03 month:03 pages:2065-2086 https://dx.doi.org/10.1007/s11590-022-01861-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 17 2022 9 03 03 2065-2086
allfieldsSound	10.1007/s11590-022-01861-1 doi (DE-627)SPR053575415 (SPR)s11590-022-01861-1-e DE-627 ger DE-627 rakwb eng Herrán, Alberto verfasserin aut A general variable neighborhood search approach for the minimum load coloring problem 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract The minimum load coloring problem consists of finding a 2-coloring function that assign either a color red or blue to each node of a graph such that the (maximum) load is minimized, i.e., to reduce as much as possible the number of edges with, at least, one endpoint colored in red (symmetrically, in blue). This %$\mathcal {NP}%$-complete problem arises in Wavelength Division Multiplexing (WDM) technology and it has been used for broadcast WDM networks. In this paper, several procedures based on the Variable Neighborhood Search (VNS) methodology are proposed and compared on a set of random graphs and DIMACS benchmarks. Experimental results show that the proposed VNS variant exhibits a remarkable performance in comparison with the state-of-the-art methods. In particular, our approach achieves the best results in 48 out of 52 considered instances by employing, on average, less than 7 seconds. These results are further confirmed by conducting statistical tests. Metaheuristics (dpeaa)DE-He213 Variable neighborhood search (dpeaa)DE-He213 Graph coloring problem (dpeaa)DE-He213 Graph partition problem (dpeaa)DE-He213 Colmenar, J. Manuel (orcid)0000-0001-7490-9450 aut Mladenović, Nenad aut Duarte, Abraham aut Enthalten in Optimization letters Berlin : Springer, 2007 17(2022), 9 vom: 03. März, Seite 2065-2086 (DE-627)534676499 (DE-600)2374345-1 1862-4480 nnns volume:17 year:2022 number:9 day:03 month:03 pages:2065-2086 https://dx.doi.org/10.1007/s11590-022-01861-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 17 2022 9 03 03 2065-2086
language	English
source	Enthalten in Optimization letters 17(2022), 9 vom: 03. März, Seite 2065-2086 volume:17 year:2022 number:9 day:03 month:03 pages:2065-2086
sourceStr	Enthalten in Optimization letters 17(2022), 9 vom: 03. März, Seite 2065-2086 volume:17 year:2022 number:9 day:03 month:03 pages:2065-2086
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Metaheuristics Variable neighborhood search Graph coloring problem Graph partition problem
isfreeaccess_bool	false
container_title	Optimization letters
authorswithroles_txt_mv	Herrán, Alberto @@aut@@ Colmenar, J. Manuel @@aut@@ Mladenović, Nenad @@aut@@ Duarte, Abraham @@aut@@
publishDateDaySort_date	2022-03-03T00:00:00Z
hierarchy_top_id	534676499
id	SPR053575415
language_de	englisch
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author	Herrán, Alberto
spellingShingle	Herrán, Alberto misc Metaheuristics misc Variable neighborhood search misc Graph coloring problem misc Graph partition problem A general variable neighborhood search approach for the minimum load coloring problem
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topic_title	A general variable neighborhood search approach for the minimum load coloring problem Metaheuristics (dpeaa)DE-He213 Variable neighborhood search (dpeaa)DE-He213 Graph coloring problem (dpeaa)DE-He213 Graph partition problem (dpeaa)DE-He213
topic	misc Metaheuristics misc Variable neighborhood search misc Graph coloring problem misc Graph partition problem
topic_unstemmed	misc Metaheuristics misc Variable neighborhood search misc Graph coloring problem misc Graph partition problem
topic_browse	misc Metaheuristics misc Variable neighborhood search misc Graph coloring problem misc Graph partition problem
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title	A general variable neighborhood search approach for the minimum load coloring problem
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title_full	A general variable neighborhood search approach for the minimum load coloring problem
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author_browse	Herrán, Alberto Colmenar, J. Manuel Mladenović, Nenad Duarte, Abraham
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title_sort	general variable neighborhood search approach for the minimum load coloring problem
title_auth	A general variable neighborhood search approach for the minimum load coloring problem
abstract	Abstract The minimum load coloring problem consists of finding a 2-coloring function that assign either a color red or blue to each node of a graph such that the (maximum) load is minimized, i.e., to reduce as much as possible the number of edges with, at least, one endpoint colored in red (symmetrically, in blue). This %$\mathcal {NP}%$-complete problem arises in Wavelength Division Multiplexing (WDM) technology and it has been used for broadcast WDM networks. In this paper, several procedures based on the Variable Neighborhood Search (VNS) methodology are proposed and compared on a set of random graphs and DIMACS benchmarks. Experimental results show that the proposed VNS variant exhibits a remarkable performance in comparison with the state-of-the-art methods. In particular, our approach achieves the best results in 48 out of 52 considered instances by employing, on average, less than 7 seconds. These results are further confirmed by conducting statistical tests. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022
abstractGer	Abstract The minimum load coloring problem consists of finding a 2-coloring function that assign either a color red or blue to each node of a graph such that the (maximum) load is minimized, i.e., to reduce as much as possible the number of edges with, at least, one endpoint colored in red (symmetrically, in blue). This %$\mathcal {NP}%$-complete problem arises in Wavelength Division Multiplexing (WDM) technology and it has been used for broadcast WDM networks. In this paper, several procedures based on the Variable Neighborhood Search (VNS) methodology are proposed and compared on a set of random graphs and DIMACS benchmarks. Experimental results show that the proposed VNS variant exhibits a remarkable performance in comparison with the state-of-the-art methods. In particular, our approach achieves the best results in 48 out of 52 considered instances by employing, on average, less than 7 seconds. These results are further confirmed by conducting statistical tests. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022
abstract_unstemmed	Abstract The minimum load coloring problem consists of finding a 2-coloring function that assign either a color red or blue to each node of a graph such that the (maximum) load is minimized, i.e., to reduce as much as possible the number of edges with, at least, one endpoint colored in red (symmetrically, in blue). This %$\mathcal {NP}%$-complete problem arises in Wavelength Division Multiplexing (WDM) technology and it has been used for broadcast WDM networks. In this paper, several procedures based on the Variable Neighborhood Search (VNS) methodology are proposed and compared on a set of random graphs and DIMACS benchmarks. Experimental results show that the proposed VNS variant exhibits a remarkable performance in comparison with the state-of-the-art methods. In particular, our approach achieves the best results in 48 out of 52 considered instances by employing, on average, less than 7 seconds. These results are further confirmed by conducting statistical tests. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022
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title_short	A general variable neighborhood search approach for the minimum load coloring problem
url	https://dx.doi.org/10.1007/s11590-022-01861-1
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doi_str	10.1007/s11590-022-01861-1
up_date	2024-07-03T20:30:55.123Z
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This %$\mathcal {NP}%$-complete problem arises in Wavelength Division Multiplexing (WDM) technology and it has been used for broadcast WDM networks. In this paper, several procedures based on the Variable Neighborhood Search (VNS) methodology are proposed and compared on a set of random graphs and DIMACS benchmarks. Experimental results show that the proposed VNS variant exhibits a remarkable performance in comparison with the state-of-the-art methods. In particular, our approach achieves the best results in 48 out of 52 considered instances by employing, on average, less than 7 seconds. 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A general variable neighborhood search approach for the minimum load coloring problem

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