Efficient wafer sorting scheduling using a hybrid artificial immune system View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-02

AUTHORS

K-C Ying, S-W Lin

ABSTRACT

The efficiency of wafer sorting scheduling is of particular importance in semiconductor fabrication, especially in the face of strong industry competition. This paper presents a novel hybrid artificial immune system (HAIS) algorithm for solving the wafer sorting scheduling problem, aimed at minimizing the total setup time and the number of testers used. To evaluate the performance of the proposed HAIS algorithm and to compare it with existing approaches, computational experiments were conducted on 480 simulation instances generated from the characteristics of a real wafer probe centre. The experimental results revealed that the proposed HAIS algorithm is highly effective and efficient, as compared with state-of-the-art algorithms on the same benchmark. More... »

PAGES

169-179

References to SciGraph publications

  • 2008-05. Solution strategies for multi-stage wafer probing scheduling problem with reentry in JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
  • 1996-10. Decomposition methods for scheduling semiconductor testing facilities in INTERNATIONAL JOURNAL OF FLEXIBLE MANUFACTURING SYSTEMS
  • 2004-11. Algorithms for the wafer probing scheduling problem with sequence-dependent set-up time and due date restrictions in JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
  • 2006-08. Study on job shop scheduling with sequence-dependent setup times using biological immune algorithm in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2008-08. A hybrid approach for single-machine tardiness problems with sequence-dependent setup times in JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
  • 2002-08. The wafer probing scheduling problem (WPSP) in JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
  • 2011-01. Meta-heuristic algorithms for wafer sorting scheduling problems in JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1057/jors.2013.8

    DOI

    http://dx.doi.org/10.1057/jors.2013.8

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1028996812


    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/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "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": "National Taipei University of Technology", 
              "id": "https://www.grid.ac/institutes/grid.412087.8", 
              "name": [
                "National Taipei University of Technology, Taipei, Taiwan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ying", 
            "givenName": "K-C", 
            "id": "sg:person.011544370416.04", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011544370416.04"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Chang Gung University", 
              "id": "https://www.grid.ac/institutes/grid.145695.a", 
              "name": [
                "Chang Gung University, Taoyuan, Taiwan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lin", 
            "givenName": "S-W", 
            "id": "sg:person.015224610754.94", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015224610754.94"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.neucom.2007.12.041", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005033486"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.eswa.2009.09.006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005926818"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-005-0022-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008307759", 
              "https://doi.org/10.1007/s00170-005-0022-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-005-0022-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008307759", 
              "https://doi.org/10.1007/s00170-005-0022-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1057/palgrave.jors.2601795", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009170284", 
              "https://doi.org/10.1057/palgrave.jors.2601795"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.asoc.2006.02.008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009993520"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/09537280110061593", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011765797"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejor.2007.02.047", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011898632"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cie.2008.09.031", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014453915"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1057/jors.2009.182", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018129066", 
              "https://doi.org/10.1057/jors.2009.182"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1057/palgrave.jors.2602354", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018788511", 
              "https://doi.org/10.1057/palgrave.jors.2602354"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.amc.2009.07.033", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019299275"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2005.03.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020334714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/0020754031000118116", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022609227"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf00170018", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026804498", 
              "https://doi.org/10.1007/bf00170018"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf00170018", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026804498", 
              "https://doi.org/10.1007/bf00170018"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/00207543.2011.588617", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027009894"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cor.2006.07.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028389862"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2007.06.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029009545"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1057/palgrave.jors.2602434", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029921411", 
              "https://doi.org/10.1057/palgrave.jors.2602434"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1057/palgrave.jors.2601362", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030964314", 
              "https://doi.org/10.1057/palgrave.jors.2601362"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.future.2004.03.014", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032505280"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/0020754032000123588", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033036578"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/00207540701484939", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033619673"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/00207540601137199", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042409206"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0377-2217(90)90215-w", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043742841"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0377-2217(90)90215-w", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043742841"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cor.2010.08.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045110666"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejor.2006.06.060", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045534810"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.amc.2005.11.136", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051187556"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/21.398686", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061122158"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/66.670181", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061206242"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2014-02", 
        "datePublishedReg": "2014-02-01", 
        "description": "The efficiency of wafer sorting scheduling is of particular importance in semiconductor fabrication, especially in the face of strong industry competition. This paper presents a novel hybrid artificial immune system (HAIS) algorithm for solving the wafer sorting scheduling problem, aimed at minimizing the total setup time and the number of testers used. To evaluate the performance of the proposed HAIS algorithm and to compare it with existing approaches, computational experiments were conducted on 480 simulation instances generated from the characteristics of a real wafer probe centre. The experimental results revealed that the proposed HAIS algorithm is highly effective and efficient, as compared with state-of-the-art algorithms on the same benchmark.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1057/jors.2013.8", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1087747", 
            "issn": [
              "0160-5682", 
              "1476-9360"
            ], 
            "name": "Journal of the Operational Research Society", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "2", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "65"
          }
        ], 
        "name": "Efficient wafer sorting scheduling using a hybrid artificial immune system", 
        "pagination": "169-179", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "8a228e8c26b626b59dbd0de0c3cbbcec6e51dca4435628de53eb9b9cfae80bd5"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1057/jors.2013.8"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1028996812"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1057/jors.2013.8", 
          "https://app.dimensions.ai/details/publication/pub.1028996812"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T01:57", 
        "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/v90/0000000001_0000000264/records_8700_00000500.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1057/jors.2013.8"
      }
    ]
     

    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.10.1057/jors.2013.8'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1057/jors.2013.8'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1057/jors.2013.8'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1057/jors.2013.8'


     

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

    165 TRIPLES      21 PREDICATES      56 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1057/jors.2013.8 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author Nae04c4a16eff4a1ba98064f40d7a5b2b
    4 schema:citation sg:pub.10.1007/bf00170018
    5 sg:pub.10.1007/s00170-005-0022-0
    6 sg:pub.10.1057/jors.2009.182
    7 sg:pub.10.1057/palgrave.jors.2601362
    8 sg:pub.10.1057/palgrave.jors.2601795
    9 sg:pub.10.1057/palgrave.jors.2602354
    10 sg:pub.10.1057/palgrave.jors.2602434
    11 https://doi.org/10.1016/0377-2217(90)90215-w
    12 https://doi.org/10.1016/j.amc.2005.11.136
    13 https://doi.org/10.1016/j.amc.2009.07.033
    14 https://doi.org/10.1016/j.asoc.2006.02.008
    15 https://doi.org/10.1016/j.cie.2008.09.031
    16 https://doi.org/10.1016/j.cor.2006.07.003
    17 https://doi.org/10.1016/j.cor.2010.08.010
    18 https://doi.org/10.1016/j.ejor.2006.06.060
    19 https://doi.org/10.1016/j.ejor.2007.02.047
    20 https://doi.org/10.1016/j.eswa.2009.09.006
    21 https://doi.org/10.1016/j.future.2004.03.014
    22 https://doi.org/10.1016/j.ins.2005.03.009
    23 https://doi.org/10.1016/j.ins.2007.06.001
    24 https://doi.org/10.1016/j.neucom.2007.12.041
    25 https://doi.org/10.1080/0020754031000118116
    26 https://doi.org/10.1080/0020754032000123588
    27 https://doi.org/10.1080/00207540601137199
    28 https://doi.org/10.1080/00207540701484939
    29 https://doi.org/10.1080/00207543.2011.588617
    30 https://doi.org/10.1080/09537280110061593
    31 https://doi.org/10.1109/21.398686
    32 https://doi.org/10.1109/66.670181
    33 schema:datePublished 2014-02
    34 schema:datePublishedReg 2014-02-01
    35 schema:description The efficiency of wafer sorting scheduling is of particular importance in semiconductor fabrication, especially in the face of strong industry competition. This paper presents a novel hybrid artificial immune system (HAIS) algorithm for solving the wafer sorting scheduling problem, aimed at minimizing the total setup time and the number of testers used. To evaluate the performance of the proposed HAIS algorithm and to compare it with existing approaches, computational experiments were conducted on 480 simulation instances generated from the characteristics of a real wafer probe centre. The experimental results revealed that the proposed HAIS algorithm is highly effective and efficient, as compared with state-of-the-art algorithms on the same benchmark.
    36 schema:genre research_article
    37 schema:inLanguage en
    38 schema:isAccessibleForFree false
    39 schema:isPartOf N0bd59c27a10946e9a9c39adad0645fec
    40 N648a5409734843e2b071c9c2f13b1159
    41 sg:journal.1087747
    42 schema:name Efficient wafer sorting scheduling using a hybrid artificial immune system
    43 schema:pagination 169-179
    44 schema:productId N23705ebb40684e11b4c3d56fa0494acf
    45 N6ab918ffd453457191e74bc92da8795a
    46 Ne682625e64de48f5a935051d548400e6
    47 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028996812
    48 https://doi.org/10.1057/jors.2013.8
    49 schema:sdDatePublished 2019-04-11T01:57
    50 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    51 schema:sdPublisher N8412c95b49c94cf0964accbd1ee76e00
    52 schema:url http://link.springer.com/10.1057/jors.2013.8
    53 sgo:license sg:explorer/license/
    54 sgo:sdDataset articles
    55 rdf:type schema:ScholarlyArticle
    56 N0bd59c27a10946e9a9c39adad0645fec schema:volumeNumber 65
    57 rdf:type schema:PublicationVolume
    58 N23705ebb40684e11b4c3d56fa0494acf schema:name doi
    59 schema:value 10.1057/jors.2013.8
    60 rdf:type schema:PropertyValue
    61 N50d58af5b9a24a43ae69316aa8eb516a rdf:first sg:person.015224610754.94
    62 rdf:rest rdf:nil
    63 N648a5409734843e2b071c9c2f13b1159 schema:issueNumber 2
    64 rdf:type schema:PublicationIssue
    65 N6ab918ffd453457191e74bc92da8795a schema:name readcube_id
    66 schema:value 8a228e8c26b626b59dbd0de0c3cbbcec6e51dca4435628de53eb9b9cfae80bd5
    67 rdf:type schema:PropertyValue
    68 N8412c95b49c94cf0964accbd1ee76e00 schema:name Springer Nature - SN SciGraph project
    69 rdf:type schema:Organization
    70 Nae04c4a16eff4a1ba98064f40d7a5b2b rdf:first sg:person.011544370416.04
    71 rdf:rest N50d58af5b9a24a43ae69316aa8eb516a
    72 Ne682625e64de48f5a935051d548400e6 schema:name dimensions_id
    73 schema:value pub.1028996812
    74 rdf:type schema:PropertyValue
    75 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    76 schema:name Information and Computing Sciences
    77 rdf:type schema:DefinedTerm
    78 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    79 schema:name Artificial Intelligence and Image Processing
    80 rdf:type schema:DefinedTerm
    81 sg:journal.1087747 schema:issn 0160-5682
    82 1476-9360
    83 schema:name Journal of the Operational Research Society
    84 rdf:type schema:Periodical
    85 sg:person.011544370416.04 schema:affiliation https://www.grid.ac/institutes/grid.412087.8
    86 schema:familyName Ying
    87 schema:givenName K-C
    88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011544370416.04
    89 rdf:type schema:Person
    90 sg:person.015224610754.94 schema:affiliation https://www.grid.ac/institutes/grid.145695.a
    91 schema:familyName Lin
    92 schema:givenName S-W
    93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015224610754.94
    94 rdf:type schema:Person
    95 sg:pub.10.1007/bf00170018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026804498
    96 https://doi.org/10.1007/bf00170018
    97 rdf:type schema:CreativeWork
    98 sg:pub.10.1007/s00170-005-0022-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008307759
    99 https://doi.org/10.1007/s00170-005-0022-0
    100 rdf:type schema:CreativeWork
    101 sg:pub.10.1057/jors.2009.182 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018129066
    102 https://doi.org/10.1057/jors.2009.182
    103 rdf:type schema:CreativeWork
    104 sg:pub.10.1057/palgrave.jors.2601362 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030964314
    105 https://doi.org/10.1057/palgrave.jors.2601362
    106 rdf:type schema:CreativeWork
    107 sg:pub.10.1057/palgrave.jors.2601795 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009170284
    108 https://doi.org/10.1057/palgrave.jors.2601795
    109 rdf:type schema:CreativeWork
    110 sg:pub.10.1057/palgrave.jors.2602354 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018788511
    111 https://doi.org/10.1057/palgrave.jors.2602354
    112 rdf:type schema:CreativeWork
    113 sg:pub.10.1057/palgrave.jors.2602434 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029921411
    114 https://doi.org/10.1057/palgrave.jors.2602434
    115 rdf:type schema:CreativeWork
    116 https://doi.org/10.1016/0377-2217(90)90215-w schema:sameAs https://app.dimensions.ai/details/publication/pub.1043742841
    117 rdf:type schema:CreativeWork
    118 https://doi.org/10.1016/j.amc.2005.11.136 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051187556
    119 rdf:type schema:CreativeWork
    120 https://doi.org/10.1016/j.amc.2009.07.033 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019299275
    121 rdf:type schema:CreativeWork
    122 https://doi.org/10.1016/j.asoc.2006.02.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009993520
    123 rdf:type schema:CreativeWork
    124 https://doi.org/10.1016/j.cie.2008.09.031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014453915
    125 rdf:type schema:CreativeWork
    126 https://doi.org/10.1016/j.cor.2006.07.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028389862
    127 rdf:type schema:CreativeWork
    128 https://doi.org/10.1016/j.cor.2010.08.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045110666
    129 rdf:type schema:CreativeWork
    130 https://doi.org/10.1016/j.ejor.2006.06.060 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045534810
    131 rdf:type schema:CreativeWork
    132 https://doi.org/10.1016/j.ejor.2007.02.047 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011898632
    133 rdf:type schema:CreativeWork
    134 https://doi.org/10.1016/j.eswa.2009.09.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005926818
    135 rdf:type schema:CreativeWork
    136 https://doi.org/10.1016/j.future.2004.03.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032505280
    137 rdf:type schema:CreativeWork
    138 https://doi.org/10.1016/j.ins.2005.03.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020334714
    139 rdf:type schema:CreativeWork
    140 https://doi.org/10.1016/j.ins.2007.06.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029009545
    141 rdf:type schema:CreativeWork
    142 https://doi.org/10.1016/j.neucom.2007.12.041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005033486
    143 rdf:type schema:CreativeWork
    144 https://doi.org/10.1080/0020754031000118116 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022609227
    145 rdf:type schema:CreativeWork
    146 https://doi.org/10.1080/0020754032000123588 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033036578
    147 rdf:type schema:CreativeWork
    148 https://doi.org/10.1080/00207540601137199 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042409206
    149 rdf:type schema:CreativeWork
    150 https://doi.org/10.1080/00207540701484939 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033619673
    151 rdf:type schema:CreativeWork
    152 https://doi.org/10.1080/00207543.2011.588617 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027009894
    153 rdf:type schema:CreativeWork
    154 https://doi.org/10.1080/09537280110061593 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011765797
    155 rdf:type schema:CreativeWork
    156 https://doi.org/10.1109/21.398686 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061122158
    157 rdf:type schema:CreativeWork
    158 https://doi.org/10.1109/66.670181 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061206242
    159 rdf:type schema:CreativeWork
    160 https://www.grid.ac/institutes/grid.145695.a schema:alternateName Chang Gung University
    161 schema:name Chang Gung University, Taoyuan, Taiwan
    162 rdf:type schema:Organization
    163 https://www.grid.ac/institutes/grid.412087.8 schema:alternateName National Taipei University of Technology
    164 schema:name National Taipei University of Technology, Taipei, Taiwan
    165 rdf:type schema:Organization
     




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


    ...