An Alternative Preference Relation to Deal with Many-Objective Optimization Problems View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Antonio L’opez , Carlos A. Coello Coello , Akira Oyama , Kozo Fujii

ABSTRACT

In this paper, we use an alternative preference relation that couples an achievement function and the ε-indicator in order to improve the scalability of a Multi-Objective Evolutionary Algorithm (moea) in many-objective optimization problems. The resulting algorithm was assessed using the Deb-Thiele-Laumanns-Zitzler (dtlz) and the Walking- Fish-Group (wfg) test suites. Our experimental results indicate that our proposed approach has a good performance even when using a high number of objectives. Regarding the dtlz test problems, their main difficulty was found to lie on the presence of dominance resistant solutions. In contrast, the hardness of wfg problems was not found to be significantly increased by adding more objectives. More... »

PAGES

291-306

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-37140-0_24

DOI

http://dx.doi.org/10.1007/978-3-642-37140-0_24

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018617843


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": "Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 252-5210, Sagamihara, Japan", 
          "id": "http://www.grid.ac/institutes/grid.450279.d", 
          "name": [
            "Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 252-5210, Sagamihara, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "L\u2019opez", 
        "givenName": "Antonio", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Departamento de Computaci\u00f3n, CINVESTAV-IPN (Evolutionary Computation Group), D.F. 07300, M\u00e9xico, M\u00e9xico", 
          "id": "http://www.grid.ac/institutes/grid.418275.d", 
          "name": [
            "Departamento de Computaci\u00f3n, CINVESTAV-IPN (Evolutionary Computation Group), D.F. 07300, M\u00e9xico, M\u00e9xico"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Coello", 
        "givenName": "Carlos A. Coello", 
        "id": "sg:person.012160505340.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012160505340.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 252-5210, Sagamihara, Japan", 
          "id": "http://www.grid.ac/institutes/grid.450279.d", 
          "name": [
            "Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 252-5210, Sagamihara, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Oyama", 
        "givenName": "Akira", 
        "id": "sg:person.010122120035.90", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010122120035.90"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 252-5210, Sagamihara, Japan", 
          "id": "http://www.grid.ac/institutes/grid.450279.d", 
          "name": [
            "Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 252-5210, Sagamihara, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fujii", 
        "givenName": "Kozo", 
        "id": "sg:person.011432545545.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011432545545.57"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2013", 
    "datePublishedReg": "2013-01-01", 
    "description": "In this paper, we use an alternative preference relation that couples an achievement function and the \u03b5-indicator in order to improve the scalability of a Multi-Objective Evolutionary Algorithm (moea) in many-objective optimization problems. The resulting algorithm was assessed using the Deb-Thiele-Laumanns-Zitzler (dtlz) and the Walking- Fish-Group (wfg) test suites. Our experimental results indicate that our proposed approach has a good performance even when using a high number of objectives. Regarding the dtlz test problems, their main difficulty was found to lie on the presence of dominance resistant solutions. In contrast, the hardness of wfg problems was not found to be significantly increased by adding more objectives.", 
    "editor": [
      {
        "familyName": "Purshouse", 
        "givenName": "Robin C.", 
        "type": "Person"
      }, 
      {
        "familyName": "Fleming", 
        "givenName": "Peter J.", 
        "type": "Person"
      }, 
      {
        "familyName": "Fonseca", 
        "givenName": "Carlos M.", 
        "type": "Person"
      }, 
      {
        "familyName": "Greco", 
        "givenName": "Salvatore", 
        "type": "Person"
      }, 
      {
        "familyName": "Shaw", 
        "givenName": "Jane", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-37140-0_24", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-642-37139-4", 
        "978-3-642-37140-0"
      ], 
      "name": "Evolutionary Multi-Criterion Optimization", 
      "type": "Book"
    }, 
    "keywords": [
      "objective optimization problems", 
      "optimization problem", 
      "multi-objective evolutionary algorithm", 
      "DTLZ test problems", 
      "dominance resistant solutions", 
      "Deb-Thiele", 
      "Laumanns-Zitzler", 
      "Walking-Fish", 
      "more objectives", 
      "test problems", 
      "evolutionary algorithm", 
      "achievement function", 
      "resistant solutions", 
      "main difficulty", 
      "preference relations", 
      "problem", 
      "algorithm", 
      "better performance", 
      "test suite", 
      "solution", 
      "experimental results", 
      "approach", 
      "scalability", 
      "objective", 
      "function", 
      "performance", 
      "number", 
      "order", 
      "difficulties", 
      "relation", 
      "results", 
      "suite", 
      "higher number", 
      "indicators", 
      "presence", 
      "contrast", 
      "hardness", 
      "paper", 
      "WFG problems", 
      "alternative preference relation", 
      "Group (wfg) test suites"
    ], 
    "name": "An Alternative Preference Relation to Deal with Many-Objective Optimization Problems", 
    "pagination": "291-306", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1018617843"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-37140-0_24"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-37140-0_24", 
      "https://app.dimensions.ai/details/publication/pub.1018617843"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2021-11-01T18:59", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211101/entities/gbq_results/chapter/chapter_404.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-642-37140-0_24"
  }
]
 

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.10.1007/978-3-642-37140-0_24'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-37140-0_24'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-37140-0_24'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-37140-0_24'


 

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

144 TRIPLES      23 PREDICATES      67 URIs      60 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-37140-0_24 schema:about anzsrc-for:01
2 anzsrc-for:0103
3 schema:author N7bdf9e523c1943c6a3d14af5a30ed98a
4 schema:datePublished 2013
5 schema:datePublishedReg 2013-01-01
6 schema:description In this paper, we use an alternative preference relation that couples an achievement function and the ε-indicator in order to improve the scalability of a Multi-Objective Evolutionary Algorithm (moea) in many-objective optimization problems. The resulting algorithm was assessed using the Deb-Thiele-Laumanns-Zitzler (dtlz) and the Walking- Fish-Group (wfg) test suites. Our experimental results indicate that our proposed approach has a good performance even when using a high number of objectives. Regarding the dtlz test problems, their main difficulty was found to lie on the presence of dominance resistant solutions. In contrast, the hardness of wfg problems was not found to be significantly increased by adding more objectives.
7 schema:editor Nf96c295421a740ccba572fc9a407fafe
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf N4ec45b75f2dd4425b4327d764e8d4ce0
12 schema:keywords DTLZ test problems
13 Deb-Thiele
14 Group (wfg) test suites
15 Laumanns-Zitzler
16 WFG problems
17 Walking-Fish
18 achievement function
19 algorithm
20 alternative preference relation
21 approach
22 better performance
23 contrast
24 difficulties
25 dominance resistant solutions
26 evolutionary algorithm
27 experimental results
28 function
29 hardness
30 higher number
31 indicators
32 main difficulty
33 more objectives
34 multi-objective evolutionary algorithm
35 number
36 objective
37 objective optimization problems
38 optimization problem
39 order
40 paper
41 performance
42 preference relations
43 presence
44 problem
45 relation
46 resistant solutions
47 results
48 scalability
49 solution
50 suite
51 test problems
52 test suite
53 schema:name An Alternative Preference Relation to Deal with Many-Objective Optimization Problems
54 schema:pagination 291-306
55 schema:productId N3d5754116be24d22a891ac5bedfd9828
56 N5c326456692e4f25895877f91bba8528
57 schema:publisher N40b33d7463774421b36d1c221900ffc6
58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018617843
59 https://doi.org/10.1007/978-3-642-37140-0_24
60 schema:sdDatePublished 2021-11-01T18:59
61 schema:sdLicense https://scigraph.springernature.com/explorer/license/
62 schema:sdPublisher N39d74158b30040b3a900ccc7bf915329
63 schema:url https://doi.org/10.1007/978-3-642-37140-0_24
64 sgo:license sg:explorer/license/
65 sgo:sdDataset chapters
66 rdf:type schema:Chapter
67 N13e5a5298a424ad8ae7eb03734449cff schema:familyName Fleming
68 schema:givenName Peter J.
69 rdf:type schema:Person
70 N16a26eec8a4a46c2b5a0f78de99cfb94 rdf:first sg:person.010122120035.90
71 rdf:rest N3724c059e95c459bac19363723f81682
72 N23c8105712ef4601a3fee4ae3c47d214 schema:familyName Greco
73 schema:givenName Salvatore
74 rdf:type schema:Person
75 N2928256f8d834c95a728bf74a210b789 rdf:first N345f452df17f46128479dba3b920f429
76 rdf:rest rdf:nil
77 N345f452df17f46128479dba3b920f429 schema:familyName Shaw
78 schema:givenName Jane
79 rdf:type schema:Person
80 N3724c059e95c459bac19363723f81682 rdf:first sg:person.011432545545.57
81 rdf:rest rdf:nil
82 N39d74158b30040b3a900ccc7bf915329 schema:name Springer Nature - SN SciGraph project
83 rdf:type schema:Organization
84 N3d5754116be24d22a891ac5bedfd9828 schema:name dimensions_id
85 schema:value pub.1018617843
86 rdf:type schema:PropertyValue
87 N40b33d7463774421b36d1c221900ffc6 schema:name Springer Nature
88 rdf:type schema:Organisation
89 N4ec45b75f2dd4425b4327d764e8d4ce0 schema:isbn 978-3-642-37139-4
90 978-3-642-37140-0
91 schema:name Evolutionary Multi-Criterion Optimization
92 rdf:type schema:Book
93 N5c326456692e4f25895877f91bba8528 schema:name doi
94 schema:value 10.1007/978-3-642-37140-0_24
95 rdf:type schema:PropertyValue
96 N6267765f4a5343afb7310d8a33fb5bef schema:familyName Purshouse
97 schema:givenName Robin C.
98 rdf:type schema:Person
99 N68f5b0fabd1f49a885f4b768d74610f5 schema:familyName Fonseca
100 schema:givenName Carlos M.
101 rdf:type schema:Person
102 N7bdf9e523c1943c6a3d14af5a30ed98a rdf:first Nd1fb27a979144082a3c72c8b26aaa80b
103 rdf:rest Na91f0162fb744916995b09b4a03c2a44
104 N8eb1fe0bff504e25b04309a9083dbd44 rdf:first N68f5b0fabd1f49a885f4b768d74610f5
105 rdf:rest Nb1af1499a0914337987ae463f2eb1649
106 Na91f0162fb744916995b09b4a03c2a44 rdf:first sg:person.012160505340.13
107 rdf:rest N16a26eec8a4a46c2b5a0f78de99cfb94
108 Nb1af1499a0914337987ae463f2eb1649 rdf:first N23c8105712ef4601a3fee4ae3c47d214
109 rdf:rest N2928256f8d834c95a728bf74a210b789
110 Nc9652887b3264bf78d72b0b47f6ce335 rdf:first N13e5a5298a424ad8ae7eb03734449cff
111 rdf:rest N8eb1fe0bff504e25b04309a9083dbd44
112 Nd1fb27a979144082a3c72c8b26aaa80b schema:affiliation grid-institutes:grid.450279.d
113 schema:familyName L’opez
114 schema:givenName Antonio
115 rdf:type schema:Person
116 Nf96c295421a740ccba572fc9a407fafe rdf:first N6267765f4a5343afb7310d8a33fb5bef
117 rdf:rest Nc9652887b3264bf78d72b0b47f6ce335
118 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
119 schema:name Mathematical Sciences
120 rdf:type schema:DefinedTerm
121 anzsrc-for:0103 schema:inDefinedTermSet anzsrc-for:
122 schema:name Numerical and Computational Mathematics
123 rdf:type schema:DefinedTerm
124 sg:person.010122120035.90 schema:affiliation grid-institutes:grid.450279.d
125 schema:familyName Oyama
126 schema:givenName Akira
127 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010122120035.90
128 rdf:type schema:Person
129 sg:person.011432545545.57 schema:affiliation grid-institutes:grid.450279.d
130 schema:familyName Fujii
131 schema:givenName Kozo
132 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011432545545.57
133 rdf:type schema:Person
134 sg:person.012160505340.13 schema:affiliation grid-institutes:grid.418275.d
135 schema:familyName Coello
136 schema:givenName Carlos A. Coello
137 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012160505340.13
138 rdf:type schema:Person
139 grid-institutes:grid.418275.d schema:alternateName Departamento de Computación, CINVESTAV-IPN (Evolutionary Computation Group), D.F. 07300, México, México
140 schema:name Departamento de Computación, CINVESTAV-IPN (Evolutionary Computation Group), D.F. 07300, México, México
141 rdf:type schema:Organization
142 grid-institutes:grid.450279.d schema:alternateName Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 252-5210, Sagamihara, Japan
143 schema:name Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 252-5210, Sagamihara, Japan
144 rdf:type schema:Organization
 




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


...