An immune algorithm with stochastic aging and kullback entropy for the chromatic number problem View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2006-12-29

AUTHORS

Vincenzo Cutello, Giuseppe Nicosia, Mario Pavone

ABSTRACT

We present a new Immune Algorithm, IMMALG, that incorporates a Stochastic Aging operator and a simple local search procedure to improve the overall performances in tackling the chromatic number problem (CNP) instances. We characterize the algorithm and set its parameters in terms of Kullback Entropy. Experiments will show that the IA we propose is very competitive with the state-of-art evolutionary algorithms. More... »

PAGES

9-33

References to SciGraph publications

  • <error retrieving object. in <ERROR RETRIEVING OBJECT
  • 2001. Pattern recognition by primary and secondary response of an Artificial Immune System in THEORY IN BIOSCIENCES
  • 2003-09. Genetic Algorithm for Graph Coloring: Exploration of Galinier and Hao's Algorithm in JOURNAL OF COMBINATORIAL OPTIMIZATION
  • 1999. Complexity and Approximation, Combinatorial Optimization Problems and Their Approximability Properties in NONE
  • 1999-12. Hybrid Evolutionary Algorithms for Graph Coloring in JOURNAL OF COMBINATORIAL OPTIMIZATION
  • 2006. An Immunological Algorithm for Global Numerical Optimization in ARTIFICIAL EVOLUTION
  • 1991-02. Graph colorings and the axiom of choice in PERIODICA MATHEMATICA HUNGARICA
  • 2005. Immune Algorithms with Aging Operators for the String Folding Problem and the Protein Folding Problem in EVOLUTIONARY COMPUTATION IN COMBINATORIAL OPTIMIZATION
  • 1999. Artificial Immune Systems and Their Applications in NONE
  • 2003. An Analysis of Solution Properties of the Graph Coloring Problem in METAHEURISTICS: COMPUTER DECISION-MAKING
  • 1998. Modern Graph Theory in NONE
  • 2004-03. Two Novel Evolutionary Formulations of the Graph Coloring Problem in JOURNAL OF COMBINATORIAL OPTIMIZATION
  • 2004. Exploring the Capability of Immune Algorithms: A Characterization of Hypermutation Operators in ARTIFICIAL IMMUNE SYSTEMS
  • 2005. Clonal Selection Algorithms: A Comparative Case Study Using Effective Mutation Potentials in ARTIFICIAL IMMUNE SYSTEMS
  • 2001-06. Pattern recognition by primary and secondary response of an Artificial Immune System in THEORY IN BIOSCIENCES
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10878-006-9036-2

    DOI

    http://dx.doi.org/10.1007/s10878-006-9036-2

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1053253130


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Mathematical Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Statistics", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy", 
              "id": "http://www.grid.ac/institutes/grid.8158.4", 
              "name": [
                "Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Cutello", 
            "givenName": "Vincenzo", 
            "id": "sg:person.013504603243.51", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013504603243.51"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy", 
              "id": "http://www.grid.ac/institutes/grid.8158.4", 
              "name": [
                "Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Nicosia", 
            "givenName": "Giuseppe", 
            "id": "sg:person.0742061443.97", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0742061443.97"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy", 
              "id": "http://www.grid.ac/institutes/grid.8158.4", 
              "name": [
                "Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Pavone", 
            "givenName": "Mario", 
            "id": "sg:person.07350620665.82", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07350620665.82"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/3-540-45105-6_23", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046153098", 
              "https://doi.org/10.1007/3-540-45105-6_23"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-31996-2_8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023662000", 
              "https://doi.org/10.1007/978-3-540-31996-2_8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-58412-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026792740", 
              "https://doi.org/10.1007/978-3-642-58412-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12064-001-0010-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000740493", 
              "https://doi.org/10.1007/s12064-001-0010-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1078/1431-7613-00032", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021912903", 
              "https://doi.org/10.1078/1431-7613-00032"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11740698_25", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011160632", 
              "https://doi.org/10.1007/11740698_25"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11536444_2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019780999", 
              "https://doi.org/10.1007/11536444_2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4612-0619-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011696368", 
              "https://doi.org/10.1007/978-1-4612-0619-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/b:joco.0000021937.26468.b2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042796995", 
              "https://doi.org/10.1023/b:joco.0000021937.26468.b2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1027312403532", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021215028", 
              "https://doi.org/10.1023/a:1027312403532"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4757-4137-7_15", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039605908", 
              "https://doi.org/10.1007/978-1-4757-4137-7_15"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02309111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035001460", 
              "https://doi.org/10.1007/bf02309111"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1009823419804", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041342329", 
              "https://doi.org/10.1023/a:1009823419804"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-59901-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038042051", 
              "https://doi.org/10.1007/978-3-642-59901-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-30220-9_22", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016285159", 
              "https://doi.org/10.1007/978-3-540-30220-9_22"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2006-12-29", 
        "datePublishedReg": "2006-12-29", 
        "description": "We present a new Immune Algorithm, IMMALG, that incorporates a Stochastic Aging operator and a simple local search procedure to improve the overall performances in tackling the chromatic number problem (CNP) instances. We characterize the algorithm and set its parameters in terms of Kullback Entropy. Experiments will show that the IA we propose is very competitive with the state-of-art evolutionary algorithms.", 
        "genre": "article", 
        "id": "sg:pub.10.1007/s10878-006-9036-2", 
        "inLanguage": "en", 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1036683", 
            "issn": [
              "1382-6905", 
              "1573-2886"
            ], 
            "name": "Journal of Combinatorial Optimization", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "14"
          }
        ], 
        "keywords": [
          "Kullback entropy", 
          "immune algorithm", 
          "art evolutionary algorithms", 
          "new immune algorithm", 
          "local search procedure", 
          "stochastic ageing", 
          "evolutionary algorithm", 
          "problem instances", 
          "chromatic number problem", 
          "search procedure", 
          "number problem", 
          "algorithm", 
          "entropy", 
          "stochastic", 
          "operators", 
          "overall performance", 
          "problem", 
          "parameters", 
          "instances", 
          "terms", 
          "performance", 
          "procedure", 
          "state", 
          "experiments", 
          "IA", 
          "aging", 
          "simple local search procedure", 
          "IMMALG", 
          "chromatic number problem (CNP) instances", 
          "number problem (CNP) instances"
        ], 
        "name": "An immune algorithm with stochastic aging and kullback entropy for the chromatic number problem", 
        "pagination": "9-33", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1053253130"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s10878-006-9036-2"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s10878-006-9036-2", 
          "https://app.dimensions.ai/details/publication/pub.1053253130"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-01-01T18:15", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_414.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1007/s10878-006-9036-2"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10878-006-9036-2'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10878-006-9036-2'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10878-006-9036-2'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10878-006-9036-2'


     

    This table displays all metadata directly associated to this object as RDF triples.

    162 TRIPLES      22 PREDICATES      70 URIs      47 LITERALS      6 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s10878-006-9036-2 schema:about anzsrc-for:01
    2 anzsrc-for:0104
    3 schema:author N91eb8010be1b46089f4bf4ae4b319f4a
    4 schema:citation sg:pub.10.1007/11536444_2
    5 sg:pub.10.1007/11740698_25
    6 sg:pub.10.1007/3-540-45105-6_23
    7 sg:pub.10.1007/978-1-4612-0619-4
    8 sg:pub.10.1007/978-1-4757-4137-7_15
    9 sg:pub.10.1007/978-3-540-30220-9_22
    10 sg:pub.10.1007/978-3-540-31996-2_8
    11 sg:pub.10.1007/978-3-642-58412-1
    12 sg:pub.10.1007/978-3-642-59901-9
    13 sg:pub.10.1007/bf02309111
    14 sg:pub.10.1007/s12064-001-0010-3
    15 sg:pub.10.1023/a:1009823419804
    16 sg:pub.10.1023/a:1027312403532
    17 sg:pub.10.1023/b:joco.0000021937.26468.b2
    18 sg:pub.10.1078/1431-7613-00032
    19 schema:datePublished 2006-12-29
    20 schema:datePublishedReg 2006-12-29
    21 schema:description We present a new Immune Algorithm, IMMALG, that incorporates a Stochastic Aging operator and a simple local search procedure to improve the overall performances in tackling the chromatic number problem (CNP) instances. We characterize the algorithm and set its parameters in terms of Kullback Entropy. Experiments will show that the IA we propose is very competitive with the state-of-art evolutionary algorithms.
    22 schema:genre article
    23 schema:inLanguage en
    24 schema:isAccessibleForFree false
    25 schema:isPartOf N039ab50dd3a440b7acb76066787b44c2
    26 N43b620b5cb7e4ff18e32b2ff7d88a186
    27 sg:journal.1036683
    28 schema:keywords IA
    29 IMMALG
    30 Kullback entropy
    31 aging
    32 algorithm
    33 art evolutionary algorithms
    34 chromatic number problem
    35 chromatic number problem (CNP) instances
    36 entropy
    37 evolutionary algorithm
    38 experiments
    39 immune algorithm
    40 instances
    41 local search procedure
    42 new immune algorithm
    43 number problem
    44 number problem (CNP) instances
    45 operators
    46 overall performance
    47 parameters
    48 performance
    49 problem
    50 problem instances
    51 procedure
    52 search procedure
    53 simple local search procedure
    54 state
    55 stochastic
    56 stochastic ageing
    57 terms
    58 schema:name An immune algorithm with stochastic aging and kullback entropy for the chromatic number problem
    59 schema:pagination 9-33
    60 schema:productId Nde6157baf67f4847b94f4f35a63e1416
    61 Ne91f64b215314dff9edf6e5743588300
    62 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053253130
    63 https://doi.org/10.1007/s10878-006-9036-2
    64 schema:sdDatePublished 2022-01-01T18:15
    65 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    66 schema:sdPublisher N78ee3324eb97427d9a5010fdee6d0647
    67 schema:url https://doi.org/10.1007/s10878-006-9036-2
    68 sgo:license sg:explorer/license/
    69 sgo:sdDataset articles
    70 rdf:type schema:ScholarlyArticle
    71 N039ab50dd3a440b7acb76066787b44c2 schema:issueNumber 1
    72 rdf:type schema:PublicationIssue
    73 N43b620b5cb7e4ff18e32b2ff7d88a186 schema:volumeNumber 14
    74 rdf:type schema:PublicationVolume
    75 N78ee3324eb97427d9a5010fdee6d0647 schema:name Springer Nature - SN SciGraph project
    76 rdf:type schema:Organization
    77 N790a2d88906a45fdb9b9aef200ada0c4 rdf:first sg:person.07350620665.82
    78 rdf:rest rdf:nil
    79 N91eb8010be1b46089f4bf4ae4b319f4a rdf:first sg:person.013504603243.51
    80 rdf:rest Nc8bd8db62637463686b4bec80993c419
    81 Nc8bd8db62637463686b4bec80993c419 rdf:first sg:person.0742061443.97
    82 rdf:rest N790a2d88906a45fdb9b9aef200ada0c4
    83 Nde6157baf67f4847b94f4f35a63e1416 schema:name dimensions_id
    84 schema:value pub.1053253130
    85 rdf:type schema:PropertyValue
    86 Ne91f64b215314dff9edf6e5743588300 schema:name doi
    87 schema:value 10.1007/s10878-006-9036-2
    88 rdf:type schema:PropertyValue
    89 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
    90 schema:name Mathematical Sciences
    91 rdf:type schema:DefinedTerm
    92 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
    93 schema:name Statistics
    94 rdf:type schema:DefinedTerm
    95 sg:journal.1036683 schema:issn 1382-6905
    96 1573-2886
    97 schema:name Journal of Combinatorial Optimization
    98 schema:publisher Springer Nature
    99 rdf:type schema:Periodical
    100 sg:person.013504603243.51 schema:affiliation grid-institutes:grid.8158.4
    101 schema:familyName Cutello
    102 schema:givenName Vincenzo
    103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013504603243.51
    104 rdf:type schema:Person
    105 sg:person.07350620665.82 schema:affiliation grid-institutes:grid.8158.4
    106 schema:familyName Pavone
    107 schema:givenName Mario
    108 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07350620665.82
    109 rdf:type schema:Person
    110 sg:person.0742061443.97 schema:affiliation grid-institutes:grid.8158.4
    111 schema:familyName Nicosia
    112 schema:givenName Giuseppe
    113 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0742061443.97
    114 rdf:type schema:Person
    115 sg:pub.10.1007/11536444_2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019780999
    116 https://doi.org/10.1007/11536444_2
    117 rdf:type schema:CreativeWork
    118 sg:pub.10.1007/11740698_25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011160632
    119 https://doi.org/10.1007/11740698_25
    120 rdf:type schema:CreativeWork
    121 sg:pub.10.1007/3-540-45105-6_23 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046153098
    122 https://doi.org/10.1007/3-540-45105-6_23
    123 rdf:type schema:CreativeWork
    124 sg:pub.10.1007/978-1-4612-0619-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011696368
    125 https://doi.org/10.1007/978-1-4612-0619-4
    126 rdf:type schema:CreativeWork
    127 sg:pub.10.1007/978-1-4757-4137-7_15 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039605908
    128 https://doi.org/10.1007/978-1-4757-4137-7_15
    129 rdf:type schema:CreativeWork
    130 sg:pub.10.1007/978-3-540-30220-9_22 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016285159
    131 https://doi.org/10.1007/978-3-540-30220-9_22
    132 rdf:type schema:CreativeWork
    133 sg:pub.10.1007/978-3-540-31996-2_8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023662000
    134 https://doi.org/10.1007/978-3-540-31996-2_8
    135 rdf:type schema:CreativeWork
    136 sg:pub.10.1007/978-3-642-58412-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026792740
    137 https://doi.org/10.1007/978-3-642-58412-1
    138 rdf:type schema:CreativeWork
    139 sg:pub.10.1007/978-3-642-59901-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038042051
    140 https://doi.org/10.1007/978-3-642-59901-9
    141 rdf:type schema:CreativeWork
    142 sg:pub.10.1007/bf02309111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035001460
    143 https://doi.org/10.1007/bf02309111
    144 rdf:type schema:CreativeWork
    145 sg:pub.10.1007/s12064-001-0010-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000740493
    146 https://doi.org/10.1007/s12064-001-0010-3
    147 rdf:type schema:CreativeWork
    148 sg:pub.10.1023/a:1009823419804 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041342329
    149 https://doi.org/10.1023/a:1009823419804
    150 rdf:type schema:CreativeWork
    151 sg:pub.10.1023/a:1027312403532 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021215028
    152 https://doi.org/10.1023/a:1027312403532
    153 rdf:type schema:CreativeWork
    154 sg:pub.10.1023/b:joco.0000021937.26468.b2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042796995
    155 https://doi.org/10.1023/b:joco.0000021937.26468.b2
    156 rdf:type schema:CreativeWork
    157 sg:pub.10.1078/1431-7613-00032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021912903
    158 https://doi.org/10.1078/1431-7613-00032
    159 rdf:type schema:CreativeWork
    160 grid-institutes:grid.8158.4 schema:alternateName Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy
    161 schema:name Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy
    162 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...