Ontology type: schema:ScholarlyArticle
2016-03-05
AUTHORS ABSTRACTMOEA/D is one of the promising evolutionary algorithms for multi- and many-objective optimization. To improve the search performance of MOEA/D, this work focuses on the solution update method in the conventional MOEA/D and proposes its alternative, the chain-reaction solution update. The proposed method is designed to maintain and improve the variable (genetic) diversity in the population by avoiding duplication of solutions in the population. In addition, the proposed method determines the order of existing solutions to be updated depending on the location of each offspring in the objective space. Furthermore, when an existing solution in the population is replaced by a new offspring, the proposed method tries to reutilize the existing solution for other search directions by recursively performing the proposed chain-reaction update procedure. This work uses discrete knapsack and continuous WFG4 problems with 2–8 objectives. Experimental results using knapsack problems show the proposed chain-reaction update contributes to improving the search performance of MOEA/D by enhancing the diversity of solutions in the objective space. In addition, experimental results using WFG4 problems show that the search performance of MOEA/D can be further improved using the proposed method. More... »
PAGES3803-3820
http://scigraph.springernature.com/pub.10.1007/s00500-016-2092-3
DOIhttp://dx.doi.org/10.1007/s00500-016-2092-3
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1034580593
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": "Faculty of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, 182-8585, Chofu, Tokyo, Japan",
"id": "http://www.grid.ac/institutes/grid.266298.1",
"name": [
"Faculty of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, 182-8585, Chofu, Tokyo, Japan"
],
"type": "Organization"
},
"familyName": "Sato",
"givenName": "Hiroyuki",
"id": "sg:person.07750750604.05",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07750750604.05"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/3-540-44719-9_6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037295160",
"https://doi.org/10.1007/3-540-44719-9_6"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-642-87563-2_5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029391184",
"https://doi.org/10.1007/978-3-642-87563-2_5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-540-30217-9_84",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006836276",
"https://doi.org/10.1007/978-3-540-30217-9_84"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-319-13563-2_24",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016612283",
"https://doi.org/10.1007/978-3-319-13563-2_24"
],
"type": "CreativeWork"
}
],
"datePublished": "2016-03-05",
"datePublishedReg": "2016-03-05",
"description": "MOEA/D is one of the promising evolutionary algorithms for multi- and many-objective optimization. To improve the search performance of MOEA/D, this work focuses on the solution update method in the conventional MOEA/D and proposes its alternative, the chain-reaction solution update. The proposed method is designed to maintain and improve the variable (genetic) diversity in the population by avoiding duplication of solutions in the population. In addition, the proposed method determines the order of existing solutions to be updated depending on the location of each offspring in the objective space. Furthermore, when an existing solution in the population is replaced by a new offspring, the proposed method tries to reutilize the existing solution for other search directions by recursively performing the proposed chain-reaction update procedure. This work uses discrete knapsack and continuous WFG4 problems with 2\u20138 objectives. Experimental results using knapsack problems show the proposed chain-reaction update contributes to improving the search performance of MOEA/D by enhancing the diversity of solutions in the objective space. In addition, experimental results using WFG4 problems show that the search performance of MOEA/D can be further improved using the proposed method.",
"genre": "article",
"id": "sg:pub.10.1007/s00500-016-2092-3",
"inLanguage": "en",
"isAccessibleForFree": false,
"isFundedItemOf": [
{
"id": "sg:grant.6155136",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1050238",
"issn": [
"1432-7643",
"1433-7479"
],
"name": "Soft Computing",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "10",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "20"
}
],
"keywords": [
"MOEA/D",
"objective space",
"solution update",
"objective optimization",
"conventional MOEA/D",
"solution update method",
"diversity of solutions",
"promising evolutionary algorithm",
"search direction",
"evolutionary algorithm",
"knapsack problem",
"search performance",
"update procedure",
"update method",
"experimental results",
"optimization",
"solution",
"new offspring",
"problem",
"space",
"knapsack",
"algorithm",
"performance",
"Multi",
"work",
"results",
"direction",
"order",
"update",
"procedure",
"variable diversity",
"objective",
"addition",
"location",
"alternative",
"effect",
"population",
"diversity",
"duplication",
"offspring",
"method"
],
"name": "Chain-reaction solution update in MOEA/D and its effects on multi- and many-objective optimization",
"pagination": "3803-3820",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1034580593"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s00500-016-2092-3"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s00500-016-2092-3",
"https://app.dimensions.ai/details/publication/pub.1034580593"
],
"sdDataset": "articles",
"sdDatePublished": "2022-05-10T10:16",
"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/article/article_701.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1007/s00500-016-2092-3"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
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/s00500-016-2092-3'
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/s00500-016-2092-3'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00500-016-2092-3'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00500-016-2092-3'
This table displays all metadata directly associated to this object as RDF triples.
117 TRIPLES
22 PREDICATES
70 URIs
58 LITERALS
6 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:pub.10.1007/s00500-016-2092-3 | schema:about | anzsrc-for:01 |
2 | ″ | ″ | anzsrc-for:0103 |
3 | ″ | schema:author | Nb1092e8d1f194119a0df2629fd826935 |
4 | ″ | schema:citation | sg:pub.10.1007/3-540-44719-9_6 |
5 | ″ | ″ | sg:pub.10.1007/978-3-319-13563-2_24 |
6 | ″ | ″ | sg:pub.10.1007/978-3-540-30217-9_84 |
7 | ″ | ″ | sg:pub.10.1007/978-3-642-87563-2_5 |
8 | ″ | schema:datePublished | 2016-03-05 |
9 | ″ | schema:datePublishedReg | 2016-03-05 |
10 | ″ | schema:description | MOEA/D is one of the promising evolutionary algorithms for multi- and many-objective optimization. To improve the search performance of MOEA/D, this work focuses on the solution update method in the conventional MOEA/D and proposes its alternative, the chain-reaction solution update. The proposed method is designed to maintain and improve the variable (genetic) diversity in the population by avoiding duplication of solutions in the population. In addition, the proposed method determines the order of existing solutions to be updated depending on the location of each offspring in the objective space. Furthermore, when an existing solution in the population is replaced by a new offspring, the proposed method tries to reutilize the existing solution for other search directions by recursively performing the proposed chain-reaction update procedure. This work uses discrete knapsack and continuous WFG4 problems with 2–8 objectives. Experimental results using knapsack problems show the proposed chain-reaction update contributes to improving the search performance of MOEA/D by enhancing the diversity of solutions in the objective space. In addition, experimental results using WFG4 problems show that the search performance of MOEA/D can be further improved using the proposed method. |
11 | ″ | schema:genre | article |
12 | ″ | schema:inLanguage | en |
13 | ″ | schema:isAccessibleForFree | false |
14 | ″ | schema:isPartOf | Nb6d84e40cd6d49528d65942212407dc4 |
15 | ″ | ″ | Ncd4be59425f74332b42bf9c1e7cf465e |
16 | ″ | ″ | sg:journal.1050238 |
17 | ″ | schema:keywords | MOEA/D |
18 | ″ | ″ | Multi |
19 | ″ | ″ | addition |
20 | ″ | ″ | algorithm |
21 | ″ | ″ | alternative |
22 | ″ | ″ | conventional MOEA/D |
23 | ″ | ″ | direction |
24 | ″ | ″ | diversity |
25 | ″ | ″ | diversity of solutions |
26 | ″ | ″ | duplication |
27 | ″ | ″ | effect |
28 | ″ | ″ | evolutionary algorithm |
29 | ″ | ″ | experimental results |
30 | ″ | ″ | knapsack |
31 | ″ | ″ | knapsack problem |
32 | ″ | ″ | location |
33 | ″ | ″ | method |
34 | ″ | ″ | new offspring |
35 | ″ | ″ | objective |
36 | ″ | ″ | objective optimization |
37 | ″ | ″ | objective space |
38 | ″ | ″ | offspring |
39 | ″ | ″ | optimization |
40 | ″ | ″ | order |
41 | ″ | ″ | performance |
42 | ″ | ″ | population |
43 | ″ | ″ | problem |
44 | ″ | ″ | procedure |
45 | ″ | ″ | promising evolutionary algorithm |
46 | ″ | ″ | results |
47 | ″ | ″ | search direction |
48 | ″ | ″ | search performance |
49 | ″ | ″ | solution |
50 | ″ | ″ | solution update |
51 | ″ | ″ | solution update method |
52 | ″ | ″ | space |
53 | ″ | ″ | update |
54 | ″ | ″ | update method |
55 | ″ | ″ | update procedure |
56 | ″ | ″ | variable diversity |
57 | ″ | ″ | work |
58 | ″ | schema:name | Chain-reaction solution update in MOEA/D and its effects on multi- and many-objective optimization |
59 | ″ | schema:pagination | 3803-3820 |
60 | ″ | schema:productId | N4f4901f113f8439c8d8bb5f7902c17df |
61 | ″ | ″ | N71036b7febb940d681501332388eff7f |
62 | ″ | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1034580593 |
63 | ″ | ″ | https://doi.org/10.1007/s00500-016-2092-3 |
64 | ″ | schema:sdDatePublished | 2022-05-10T10:16 |
65 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
66 | ″ | schema:sdPublisher | Nfe7f3e0518034688816c3c54da8e0eb3 |
67 | ″ | schema:url | https://doi.org/10.1007/s00500-016-2092-3 |
68 | ″ | sgo:license | sg:explorer/license/ |
69 | ″ | sgo:sdDataset | articles |
70 | ″ | rdf:type | schema:ScholarlyArticle |
71 | N4f4901f113f8439c8d8bb5f7902c17df | schema:name | dimensions_id |
72 | ″ | schema:value | pub.1034580593 |
73 | ″ | rdf:type | schema:PropertyValue |
74 | N71036b7febb940d681501332388eff7f | schema:name | doi |
75 | ″ | schema:value | 10.1007/s00500-016-2092-3 |
76 | ″ | rdf:type | schema:PropertyValue |
77 | Nb1092e8d1f194119a0df2629fd826935 | rdf:first | sg:person.07750750604.05 |
78 | ″ | rdf:rest | rdf:nil |
79 | Nb6d84e40cd6d49528d65942212407dc4 | schema:volumeNumber | 20 |
80 | ″ | rdf:type | schema:PublicationVolume |
81 | Ncd4be59425f74332b42bf9c1e7cf465e | schema:issueNumber | 10 |
82 | ″ | rdf:type | schema:PublicationIssue |
83 | Nfe7f3e0518034688816c3c54da8e0eb3 | schema:name | Springer Nature - SN SciGraph project |
84 | ″ | rdf:type | schema:Organization |
85 | anzsrc-for:01 | schema:inDefinedTermSet | anzsrc-for: |
86 | ″ | schema:name | Mathematical Sciences |
87 | ″ | rdf:type | schema:DefinedTerm |
88 | anzsrc-for:0103 | schema:inDefinedTermSet | anzsrc-for: |
89 | ″ | schema:name | Numerical and Computational Mathematics |
90 | ″ | rdf:type | schema:DefinedTerm |
91 | sg:grant.6155136 | http://pending.schema.org/fundedItem | sg:pub.10.1007/s00500-016-2092-3 |
92 | ″ | rdf:type | schema:MonetaryGrant |
93 | sg:journal.1050238 | schema:issn | 1432-7643 |
94 | ″ | ″ | 1433-7479 |
95 | ″ | schema:name | Soft Computing |
96 | ″ | schema:publisher | Springer Nature |
97 | ″ | rdf:type | schema:Periodical |
98 | sg:person.07750750604.05 | schema:affiliation | grid-institutes:grid.266298.1 |
99 | ″ | schema:familyName | Sato |
100 | ″ | schema:givenName | Hiroyuki |
101 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07750750604.05 |
102 | ″ | rdf:type | schema:Person |
103 | sg:pub.10.1007/3-540-44719-9_6 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1037295160 |
104 | ″ | ″ | https://doi.org/10.1007/3-540-44719-9_6 |
105 | ″ | rdf:type | schema:CreativeWork |
106 | sg:pub.10.1007/978-3-319-13563-2_24 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1016612283 |
107 | ″ | ″ | https://doi.org/10.1007/978-3-319-13563-2_24 |
108 | ″ | rdf:type | schema:CreativeWork |
109 | sg:pub.10.1007/978-3-540-30217-9_84 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1006836276 |
110 | ″ | ″ | https://doi.org/10.1007/978-3-540-30217-9_84 |
111 | ″ | rdf:type | schema:CreativeWork |
112 | sg:pub.10.1007/978-3-642-87563-2_5 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1029391184 |
113 | ″ | ″ | https://doi.org/10.1007/978-3-642-87563-2_5 |
114 | ″ | rdf:type | schema:CreativeWork |
115 | grid-institutes:grid.266298.1 | schema:alternateName | Faculty of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, 182-8585, Chofu, Tokyo, Japan |
116 | ″ | schema:name | Faculty of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, 182-8585, Chofu, Tokyo, Japan |
117 | ″ | rdf:type | schema:Organization |