Interval-Valued Atanassov Intuitionistic Fuzzy CODAS Method for Multi Criteria Group Decision Making Problems View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Fatma Betül Yeni, Gökhan Özçelik

ABSTRACT

The paper presents a fuzzy extension of CODAS (COmbinative Distance-Based ASsessment) method which is called as interval-valued Atanassov intuitionistic fuzzy CODAS (IVAIF-CODAS) method for group decision making processes. The extended method considers interval-valued Atanassov intuitionistic fuzzy sets (IVAIFSs) to define the judgements of decision-makers and uses interval-valued Atanassov intuitionistic fuzzy weighted aggregation operator to aggregate the evaluations of decision makers. Due to the abilities of IVAIFS in modeling of uncertainty, the extended method can be readily applied to many decision problems under fuzzy circumstances. In the study, a personnel selection problem is handled to show applicability of the IVAIF-CODAS method. Computational analysis is performed by using three different well-known IVAIF-based multi criteria group decision making (MCGDM) methods in order to test the stability and validity of the outputs. The proposed method is an easy to use and an effective tool in terms of producing as robust results as other methods and requiring relatively less effort. More... »

PAGES

433-452

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10726-018-9603-9

DOI

http://dx.doi.org/10.1007/s10726-018-9603-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110535727


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/2008/0806", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information Systems", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Karadeniz Technical University", 
          "id": "https://www.grid.ac/institutes/grid.31564.35", 
          "name": [
            "Department of Industrial Engineering, Faculty of Engineering, Karadeniz Technical University, 61080, Ortahisar, Trabzon, Turkey"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yeni", 
        "givenName": "Fatma Bet\u00fcl", 
        "id": "sg:person.013601261513.90", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013601261513.90"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Karadeniz Technical University", 
          "id": "https://www.grid.ac/institutes/grid.31564.35", 
          "name": [
            "Department of Industrial Engineering, Faculty of Engineering, Karadeniz Technical University, 61080, Ortahisar, Trabzon, Turkey"
          ], 
          "type": "Organization"
        }, 
        "familyName": "\u00d6z\u00e7elik", 
        "givenName": "G\u00f6khan", 
        "id": "sg:person.012405015660.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012405015660.04"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s00500-014-1519-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000181891", 
          "https://doi.org/10.1007/s00500-014-1519-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/1742-6596/96/1/012089", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001335409"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.asoc.2014.08.073", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001508737"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2010.12.096", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002532827"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ins.2014.05.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003544728"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1874-8651(08)60026-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004996809"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2013/656879", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005190947"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-0114(89)90205-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006558755"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-0114(89)90205-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006558755"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2010.08.092", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007386559"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0019-9958(65)90241-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009640697"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.asoc.2011.01.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011729362"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.knosys.2011.08.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014226113"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0165-0114(86)80034-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015317579"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2010.03.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015954195"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10700-014-9195-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016704356", 
          "https://doi.org/10.1007/s10700-014-9195-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.apm.2015.08.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017281755"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00500-010-0563-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018569138", 
          "https://doi.org/10.1007/s00500-010-0563-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2015/560690", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020694718"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/18756891.2016.1144152", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031503620"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cie.2013.03.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034265488"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2012/407942", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034278105"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10700-011-9102-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039085323", 
          "https://doi.org/10.1007/s10700-011-9102-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.energy.2015.06.086", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040186329"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.asoc.2014.08.031", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042141826"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tfuzz.2010.2041009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061606334"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/mnsc.17.4.b141", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064716797"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3846/20294913.2012.762953", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071468177"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4028/www.scientific.net/amm.357-360.2703", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071936174"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3846/16111699.2016.1278559", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083728363"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3846/16486897.2017.1281139", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084442275"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1504/ijpm.2017.086399", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091662957"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/fskd.2007.427", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093968814"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/fskd.2008.581", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094185452"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1515/jisys-2017-0363", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100906469"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5267/j.msl.2018.1.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100937628"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iciea.2017.8282849", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100940503"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.asoc.2018.04.040", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103809269"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1108/jeim-01-2018-0001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1104413474"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1108/jeim-01-2018-0020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1104413476"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00500-018-3317-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105149321", 
          "https://doi.org/10.1007/s00500-018-3317-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00500-018-3317-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105149321", 
          "https://doi.org/10.1007/s00500-018-3317-4"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-04", 
    "datePublishedReg": "2019-04-01", 
    "description": "The paper presents a fuzzy extension of CODAS (COmbinative Distance-Based ASsessment) method which is called as interval-valued Atanassov intuitionistic fuzzy CODAS (IVAIF-CODAS) method for group decision making processes. The extended method considers interval-valued Atanassov intuitionistic fuzzy sets (IVAIFSs) to define the judgements of decision-makers and uses interval-valued Atanassov intuitionistic fuzzy weighted aggregation operator to aggregate the evaluations of decision makers. Due to the abilities of IVAIFS in modeling of uncertainty, the extended method can be readily applied to many decision problems under fuzzy circumstances. In the study, a personnel selection problem is handled to show applicability of the IVAIF-CODAS method. Computational analysis is performed by using three different well-known IVAIF-based multi criteria group decision making (MCGDM) methods in order to test the stability and validity of the outputs. The proposed method is an easy to use and an effective tool in terms of producing as robust results as other methods and requiring relatively less effort.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10726-018-9603-9", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136143", 
        "issn": [
          "0926-2644", 
          "1572-9907"
        ], 
        "name": "Group Decision and Negotiation", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "28"
      }
    ], 
    "name": "Interval-Valued Atanassov Intuitionistic Fuzzy CODAS Method for Multi Criteria Group Decision Making Problems", 
    "pagination": "433-452", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "64022e86f3ab4c256745bfe4e7b3327893dbf39853dfc696102d0ecfacb6bc1c"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10726-018-9603-9"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1110535727"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10726-018-9603-9", 
      "https://app.dimensions.ai/details/publication/pub.1110535727"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:26", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000362_0000000362/records_87109_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs10726-018-9603-9"
  }
]
 

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/s10726-018-9603-9'

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/s10726-018-9603-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10726-018-9603-9'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10726-018-9603-9'


 

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

193 TRIPLES      21 PREDICATES      67 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10726-018-9603-9 schema:about anzsrc-for:08
2 anzsrc-for:0806
3 schema:author Nfbb0c62fbdcf4060b3018403dd8b524c
4 schema:citation sg:pub.10.1007/s00500-010-0563-5
5 sg:pub.10.1007/s00500-014-1519-y
6 sg:pub.10.1007/s00500-018-3317-4
7 sg:pub.10.1007/s10700-011-9102-9
8 sg:pub.10.1007/s10700-014-9195-z
9 https://doi.org/10.1016/0165-0114(89)90205-4
10 https://doi.org/10.1016/j.apm.2015.08.011
11 https://doi.org/10.1016/j.asoc.2011.01.011
12 https://doi.org/10.1016/j.asoc.2014.08.031
13 https://doi.org/10.1016/j.asoc.2014.08.073
14 https://doi.org/10.1016/j.asoc.2018.04.040
15 https://doi.org/10.1016/j.cie.2013.03.002
16 https://doi.org/10.1016/j.energy.2015.06.086
17 https://doi.org/10.1016/j.eswa.2010.03.013
18 https://doi.org/10.1016/j.eswa.2010.08.092
19 https://doi.org/10.1016/j.eswa.2010.12.096
20 https://doi.org/10.1016/j.ins.2014.05.018
21 https://doi.org/10.1016/j.knosys.2011.08.005
22 https://doi.org/10.1016/s0019-9958(65)90241-x
23 https://doi.org/10.1016/s0165-0114(86)80034-3
24 https://doi.org/10.1016/s1874-8651(08)60026-5
25 https://doi.org/10.1080/18756891.2016.1144152
26 https://doi.org/10.1088/1742-6596/96/1/012089
27 https://doi.org/10.1108/jeim-01-2018-0001
28 https://doi.org/10.1108/jeim-01-2018-0020
29 https://doi.org/10.1109/fskd.2007.427
30 https://doi.org/10.1109/fskd.2008.581
31 https://doi.org/10.1109/iciea.2017.8282849
32 https://doi.org/10.1109/tfuzz.2010.2041009
33 https://doi.org/10.1155/2012/407942
34 https://doi.org/10.1155/2013/656879
35 https://doi.org/10.1155/2015/560690
36 https://doi.org/10.1287/mnsc.17.4.b141
37 https://doi.org/10.1504/ijpm.2017.086399
38 https://doi.org/10.1515/jisys-2017-0363
39 https://doi.org/10.3846/16111699.2016.1278559
40 https://doi.org/10.3846/16486897.2017.1281139
41 https://doi.org/10.3846/20294913.2012.762953
42 https://doi.org/10.4028/www.scientific.net/amm.357-360.2703
43 https://doi.org/10.5267/j.msl.2018.1.004
44 schema:datePublished 2019-04
45 schema:datePublishedReg 2019-04-01
46 schema:description The paper presents a fuzzy extension of CODAS (COmbinative Distance-Based ASsessment) method which is called as interval-valued Atanassov intuitionistic fuzzy CODAS (IVAIF-CODAS) method for group decision making processes. The extended method considers interval-valued Atanassov intuitionistic fuzzy sets (IVAIFSs) to define the judgements of decision-makers and uses interval-valued Atanassov intuitionistic fuzzy weighted aggregation operator to aggregate the evaluations of decision makers. Due to the abilities of IVAIFS in modeling of uncertainty, the extended method can be readily applied to many decision problems under fuzzy circumstances. In the study, a personnel selection problem is handled to show applicability of the IVAIF-CODAS method. Computational analysis is performed by using three different well-known IVAIF-based multi criteria group decision making (MCGDM) methods in order to test the stability and validity of the outputs. The proposed method is an easy to use and an effective tool in terms of producing as robust results as other methods and requiring relatively less effort.
47 schema:genre research_article
48 schema:inLanguage en
49 schema:isAccessibleForFree false
50 schema:isPartOf N5d6f921385dd4e05bd680e06689b6171
51 Ncad2b3fb56d8451485769445678f3038
52 sg:journal.1136143
53 schema:name Interval-Valued Atanassov Intuitionistic Fuzzy CODAS Method for Multi Criteria Group Decision Making Problems
54 schema:pagination 433-452
55 schema:productId N24e5e69fb47c495caf3d3e0e462a0e04
56 N73c0097f36174ec4b388969dae8aac34
57 N8487b3fa71ba4088b7d295e92bbe853b
58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110535727
59 https://doi.org/10.1007/s10726-018-9603-9
60 schema:sdDatePublished 2019-04-11T12:26
61 schema:sdLicense https://scigraph.springernature.com/explorer/license/
62 schema:sdPublisher N0f454a4a3f2d4e69ab420831dea8ee03
63 schema:url https://link.springer.com/10.1007%2Fs10726-018-9603-9
64 sgo:license sg:explorer/license/
65 sgo:sdDataset articles
66 rdf:type schema:ScholarlyArticle
67 N0f454a4a3f2d4e69ab420831dea8ee03 schema:name Springer Nature - SN SciGraph project
68 rdf:type schema:Organization
69 N24ac6f543f714db1a1e7011984662a2f rdf:first sg:person.012405015660.04
70 rdf:rest rdf:nil
71 N24e5e69fb47c495caf3d3e0e462a0e04 schema:name dimensions_id
72 schema:value pub.1110535727
73 rdf:type schema:PropertyValue
74 N5d6f921385dd4e05bd680e06689b6171 schema:issueNumber 2
75 rdf:type schema:PublicationIssue
76 N73c0097f36174ec4b388969dae8aac34 schema:name readcube_id
77 schema:value 64022e86f3ab4c256745bfe4e7b3327893dbf39853dfc696102d0ecfacb6bc1c
78 rdf:type schema:PropertyValue
79 N8487b3fa71ba4088b7d295e92bbe853b schema:name doi
80 schema:value 10.1007/s10726-018-9603-9
81 rdf:type schema:PropertyValue
82 Ncad2b3fb56d8451485769445678f3038 schema:volumeNumber 28
83 rdf:type schema:PublicationVolume
84 Nfbb0c62fbdcf4060b3018403dd8b524c rdf:first sg:person.013601261513.90
85 rdf:rest N24ac6f543f714db1a1e7011984662a2f
86 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
87 schema:name Information and Computing Sciences
88 rdf:type schema:DefinedTerm
89 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
90 schema:name Information Systems
91 rdf:type schema:DefinedTerm
92 sg:journal.1136143 schema:issn 0926-2644
93 1572-9907
94 schema:name Group Decision and Negotiation
95 rdf:type schema:Periodical
96 sg:person.012405015660.04 schema:affiliation https://www.grid.ac/institutes/grid.31564.35
97 schema:familyName Özçelik
98 schema:givenName Gökhan
99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012405015660.04
100 rdf:type schema:Person
101 sg:person.013601261513.90 schema:affiliation https://www.grid.ac/institutes/grid.31564.35
102 schema:familyName Yeni
103 schema:givenName Fatma Betül
104 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013601261513.90
105 rdf:type schema:Person
106 sg:pub.10.1007/s00500-010-0563-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018569138
107 https://doi.org/10.1007/s00500-010-0563-5
108 rdf:type schema:CreativeWork
109 sg:pub.10.1007/s00500-014-1519-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1000181891
110 https://doi.org/10.1007/s00500-014-1519-y
111 rdf:type schema:CreativeWork
112 sg:pub.10.1007/s00500-018-3317-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105149321
113 https://doi.org/10.1007/s00500-018-3317-4
114 rdf:type schema:CreativeWork
115 sg:pub.10.1007/s10700-011-9102-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039085323
116 https://doi.org/10.1007/s10700-011-9102-9
117 rdf:type schema:CreativeWork
118 sg:pub.10.1007/s10700-014-9195-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1016704356
119 https://doi.org/10.1007/s10700-014-9195-z
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1016/0165-0114(89)90205-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006558755
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1016/j.apm.2015.08.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017281755
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/j.asoc.2011.01.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011729362
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/j.asoc.2014.08.031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042141826
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.asoc.2014.08.073 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001508737
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.asoc.2018.04.040 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103809269
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/j.cie.2013.03.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034265488
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1016/j.energy.2015.06.086 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040186329
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/j.eswa.2010.03.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015954195
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/j.eswa.2010.08.092 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007386559
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/j.eswa.2010.12.096 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002532827
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.ins.2014.05.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003544728
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/j.knosys.2011.08.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014226113
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/s0019-9958(65)90241-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1009640697
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/s0165-0114(86)80034-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015317579
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1016/s1874-8651(08)60026-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004996809
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1080/18756891.2016.1144152 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031503620
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1088/1742-6596/96/1/012089 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001335409
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1108/jeim-01-2018-0001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104413474
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1108/jeim-01-2018-0020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104413476
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1109/fskd.2007.427 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093968814
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1109/fskd.2008.581 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094185452
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1109/iciea.2017.8282849 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100940503
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1109/tfuzz.2010.2041009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061606334
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1155/2012/407942 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034278105
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1155/2013/656879 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005190947
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1155/2015/560690 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020694718
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1287/mnsc.17.4.b141 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064716797
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1504/ijpm.2017.086399 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091662957
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1515/jisys-2017-0363 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100906469
180 rdf:type schema:CreativeWork
181 https://doi.org/10.3846/16111699.2016.1278559 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083728363
182 rdf:type schema:CreativeWork
183 https://doi.org/10.3846/16486897.2017.1281139 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084442275
184 rdf:type schema:CreativeWork
185 https://doi.org/10.3846/20294913.2012.762953 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071468177
186 rdf:type schema:CreativeWork
187 https://doi.org/10.4028/www.scientific.net/amm.357-360.2703 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071936174
188 rdf:type schema:CreativeWork
189 https://doi.org/10.5267/j.msl.2018.1.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100937628
190 rdf:type schema:CreativeWork
191 https://www.grid.ac/institutes/grid.31564.35 schema:alternateName Karadeniz Technical University
192 schema:name Department of Industrial Engineering, Faculty of Engineering, Karadeniz Technical University, 61080, Ortahisar, Trabzon, Turkey
193 rdf:type schema:Organization
 




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


...