Introducing the Environment in Ant Colony Optimization View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016-07-16

AUTHORS

Antonio Mucherino , Stefka Fidanova , Maria Ganzha

ABSTRACT

Meta-heuristicsaregeneral-purpose methods for global optimization, which take generally inspiration from natural behaviors and phenomena. Among the others, Ant Colony Optimization (ACO) received particular interest in the last years. In this work, we introduce the environment in ACO, for the meta-heuristic to perform a more realistic simulation of the ants’ behavior. Computational experiments on instances of the GPS Surveying Problem (GSP) show that the introduction of the environment in ACO allows us to improve the quality of obtained solutions. More... »

PAGES

147-158

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-40132-4_9

DOI

http://dx.doi.org/10.1007/978-3-319-40132-4_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1019154870


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/2008/0103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Numerical and Computational Mathematics", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "IRISA, University of Rennes 1, Rennes, France", 
          "id": "http://www.grid.ac/institutes/grid.420225.3", 
          "name": [
            "IRISA, University of Rennes 1, Rennes, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mucherino", 
        "givenName": "Antonio", 
        "id": "sg:person.014026074116.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014026074116.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "BAS, University of Sofia, Sofia, Bulgaria", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "BAS, University of Sofia, Sofia, Bulgaria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fidanova", 
        "givenName": "Stefka", 
        "id": "sg:person.011173106320.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011173106320.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "SRI, Polish Academy of Science, Warsaw, Poland", 
          "id": "http://www.grid.ac/institutes/grid.413454.3", 
          "name": [
            "SRI, Polish Academy of Science, Warsaw, Poland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ganzha", 
        "givenName": "Maria", 
        "id": "sg:person.012054343730.36", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012054343730.36"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2016-07-16", 
    "datePublishedReg": "2016-07-16", 
    "description": "Meta-heuristicsaregeneral-purpose methods for global optimization, which take generally inspiration from natural behaviors and phenomena. Among the others, Ant Colony Optimization (ACO) received particular interest in the last years. In this work, we introduce the environment in ACO, for the meta-heuristic to perform a more realistic simulation of the ants\u2019 behavior. Computational experiments on instances of the GPS Surveying Problem (GSP) show that the introduction of the environment in ACO allows us to improve the quality of obtained solutions.", 
    "editor": [
      {
        "familyName": "Fidanova", 
        "givenName": "Stefka", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-40132-4_9", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-319-40131-7", 
        "978-3-319-40132-4"
      ], 
      "name": "Recent Advances in Computational Optimization", 
      "type": "Book"
    }, 
    "keywords": [
      "Ant Colony Optimization", 
      "colony optimization", 
      "global optimization", 
      "computational experiments", 
      "purpose method", 
      "surveying problems", 
      "GPS Surveying Problem", 
      "optimization", 
      "realistic simulation", 
      "particular interest", 
      "simulations", 
      "problem", 
      "solution", 
      "natural behavior", 
      "behavior", 
      "phenomenon", 
      "instances", 
      "last years", 
      "work", 
      "experiments", 
      "interest", 
      "introduction", 
      "environment", 
      "inspiration", 
      "ants", 
      "quality", 
      "years", 
      "method"
    ], 
    "name": "Introducing the Environment in Ant Colony Optimization", 
    "pagination": "147-158", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1019154870"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-40132-4_9"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-40132-4_9", 
      "https://app.dimensions.ai/details/publication/pub.1019154870"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-05-10T10:55", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/chapter/chapter_67.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-319-40132-4_9"
  }
]
 

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.10.1007/978-3-319-40132-4_9'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-40132-4_9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-40132-4_9'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-40132-4_9'


 

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

108 TRIPLES      23 PREDICATES      53 URIs      46 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-40132-4_9 schema:about anzsrc-for:01
2 anzsrc-for:0103
3 schema:author Ne64d89e632674f3291fb01c63ac4be2e
4 schema:datePublished 2016-07-16
5 schema:datePublishedReg 2016-07-16
6 schema:description Meta-heuristicsaregeneral-purpose methods for global optimization, which take generally inspiration from natural behaviors and phenomena. Among the others, Ant Colony Optimization (ACO) received particular interest in the last years. In this work, we introduce the environment in ACO, for the meta-heuristic to perform a more realistic simulation of the ants’ behavior. Computational experiments on instances of the GPS Surveying Problem (GSP) show that the introduction of the environment in ACO allows us to improve the quality of obtained solutions.
7 schema:editor N8e6adc9776b4431f9f5ea3a638497c92
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf Ncb7b1db568f5475bb453dfee571859a7
12 schema:keywords Ant Colony Optimization
13 GPS Surveying Problem
14 ants
15 behavior
16 colony optimization
17 computational experiments
18 environment
19 experiments
20 global optimization
21 inspiration
22 instances
23 interest
24 introduction
25 last years
26 method
27 natural behavior
28 optimization
29 particular interest
30 phenomenon
31 problem
32 purpose method
33 quality
34 realistic simulation
35 simulations
36 solution
37 surveying problems
38 work
39 years
40 schema:name Introducing the Environment in Ant Colony Optimization
41 schema:pagination 147-158
42 schema:productId N0b35c60d1df44fdea7c82e98905be8d4
43 Ne36b91c5bcb54194a7aacd969d20e710
44 schema:publisher Nc886c38b84e2414085eb31a2f043988b
45 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019154870
46 https://doi.org/10.1007/978-3-319-40132-4_9
47 schema:sdDatePublished 2022-05-10T10:55
48 schema:sdLicense https://scigraph.springernature.com/explorer/license/
49 schema:sdPublisher N6c643b19fbf84de4ba9306b7e4088ea9
50 schema:url https://doi.org/10.1007/978-3-319-40132-4_9
51 sgo:license sg:explorer/license/
52 sgo:sdDataset chapters
53 rdf:type schema:Chapter
54 N0b35c60d1df44fdea7c82e98905be8d4 schema:name dimensions_id
55 schema:value pub.1019154870
56 rdf:type schema:PropertyValue
57 N0f61e95a10cb4c2eb2619e4f251b125c schema:familyName Fidanova
58 schema:givenName Stefka
59 rdf:type schema:Person
60 N670c1205a58e4b158a6490485b630b90 rdf:first sg:person.011173106320.18
61 rdf:rest Nb4c2c6ef7752429ab74cf0c23f90e96c
62 N6c643b19fbf84de4ba9306b7e4088ea9 schema:name Springer Nature - SN SciGraph project
63 rdf:type schema:Organization
64 N8e6adc9776b4431f9f5ea3a638497c92 rdf:first N0f61e95a10cb4c2eb2619e4f251b125c
65 rdf:rest rdf:nil
66 Nb4c2c6ef7752429ab74cf0c23f90e96c rdf:first sg:person.012054343730.36
67 rdf:rest rdf:nil
68 Nc886c38b84e2414085eb31a2f043988b schema:name Springer Nature
69 rdf:type schema:Organisation
70 Ncb7b1db568f5475bb453dfee571859a7 schema:isbn 978-3-319-40131-7
71 978-3-319-40132-4
72 schema:name Recent Advances in Computational Optimization
73 rdf:type schema:Book
74 Ne36b91c5bcb54194a7aacd969d20e710 schema:name doi
75 schema:value 10.1007/978-3-319-40132-4_9
76 rdf:type schema:PropertyValue
77 Ne64d89e632674f3291fb01c63ac4be2e rdf:first sg:person.014026074116.42
78 rdf:rest N670c1205a58e4b158a6490485b630b90
79 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
80 schema:name Mathematical Sciences
81 rdf:type schema:DefinedTerm
82 anzsrc-for:0103 schema:inDefinedTermSet anzsrc-for:
83 schema:name Numerical and Computational Mathematics
84 rdf:type schema:DefinedTerm
85 sg:person.011173106320.18 schema:affiliation grid-institutes:None
86 schema:familyName Fidanova
87 schema:givenName Stefka
88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011173106320.18
89 rdf:type schema:Person
90 sg:person.012054343730.36 schema:affiliation grid-institutes:grid.413454.3
91 schema:familyName Ganzha
92 schema:givenName Maria
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012054343730.36
94 rdf:type schema:Person
95 sg:person.014026074116.42 schema:affiliation grid-institutes:grid.420225.3
96 schema:familyName Mucherino
97 schema:givenName Antonio
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014026074116.42
99 rdf:type schema:Person
100 grid-institutes:None schema:alternateName BAS, University of Sofia, Sofia, Bulgaria
101 schema:name BAS, University of Sofia, Sofia, Bulgaria
102 rdf:type schema:Organization
103 grid-institutes:grid.413454.3 schema:alternateName SRI, Polish Academy of Science, Warsaw, Poland
104 schema:name SRI, Polish Academy of Science, Warsaw, Poland
105 rdf:type schema:Organization
106 grid-institutes:grid.420225.3 schema:alternateName IRISA, University of Rennes 1, Rennes, France
107 schema:name IRISA, University of Rennes 1, Rennes, France
108 rdf:type schema:Organization
 




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


...