A genetic-algorithm-based approach to the two-echelon capacitated vehicle routing problem with stochastic demands in logistics service View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-11

AUTHORS

Kangzhou Wang, Shulin Lan, Yingxue Zhao

ABSTRACT

This paper addresses the two-echelon capacitated vehicle routing problem (2E-CVRP) with stochastic demands (2E-CVRPSD) in city logistics. A stochastic program with recourse is used to describe the problem. This program aims to minimize the sum of the travel cost and the expected cost of recourse actions resulting from potential route failures. In a two-echelon distribution system, split deliveries are allowed at the first level but not at the second level, thereby increasing the difficulty of calculating the expected failure cost. Three types of routes with or without split deliveries are identified. Different methods are devised or adapted from the literature to compute the failure cost. A genetic-algorithm-based (GA) approach is proposed to solve the 2E-CVRPSD. A simple encoding and decoding scheme, a modified route copy crossover operator, and a satellite-selection-based mutation operator are devised in this approach. The numerical results show that for all instances, the expected cost of the best 2E-CVRPSD solution found by the proposed approach is not greater than that of the best-known 2E-CVRP solution with an average relative gap of 2.57%. Therefore, the GA-based approach can find high-quality solutions for the 2E-CVRPSD. More... »

PAGES

1409-1421

Identifiers

URI

http://scigraph.springernature.com/pub.10.1057/s41274-016-0170-7

DOI

http://dx.doi.org/10.1057/s41274-016-0170-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1074200968


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/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Lanzhou University", 
          "id": "https://www.grid.ac/institutes/grid.32566.34", 
          "name": [
            "School of Management, Lanzhou University, Lanzhou, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Kangzhou", 
        "id": "sg:person.010615416167.17", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010615416167.17"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Hong Kong", 
          "id": "https://www.grid.ac/institutes/grid.194645.b", 
          "name": [
            "Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lan", 
        "givenName": "Shulin", 
        "id": "sg:person.013206644677.93", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013206644677.93"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of International Business and Economics", 
          "id": "https://www.grid.ac/institutes/grid.443284.d", 
          "name": [
            "School of International Trade and Economics, University of International Business and Economics, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhao", 
        "givenName": "Yingxue", 
        "id": "sg:person.012446563503.49", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012446563503.49"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.ijpe.2010.01.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000461499"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/00207543.2011.622310", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002129394"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.asoc.2013.01.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005128741"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1057/jors.2015.19", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005684925", 
          "https://doi.org/10.1057/jors.2015.19"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4614-6322-1_7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008057272", 
          "https://doi.org/10.1007/978-1-4614-6322-1_7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cor.2014.07.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010267688"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10852-005-9033-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011557734", 
          "https://doi.org/10.1007/s10852-005-9033-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10852-005-9033-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011557734", 
          "https://doi.org/10.1007/s10852-005-9033-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0377-2217(80)90124-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015061066"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0377-2217(80)90124-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015061066"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.endm.2010.05.081", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017979035"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1057/jors.2014.88", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021669263", 
          "https://doi.org/10.1057/jors.2014.88"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cor.2012.10.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026845388"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-20364-0_16", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030173503", 
          "https://doi.org/10.1007/978-3-642-20364-0_16"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-20364-0_16", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030173503", 
          "https://doi.org/10.1007/978-3-642-20364-0_16"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cor.2012.04.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031623177"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.orl.2006.12.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034668731"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11590-012-0568-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035853361", 
          "https://doi.org/10.1007/s11590-012-0568-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/0305215x.2014.928818", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036727453"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cor.2014.06.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037802915"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11067-013-9190-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039454786", 
          "https://doi.org/10.1007/s11067-013-9190-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2014/517467", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046171756"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0305-0548(03)00158-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048382071"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0305-0548(03)00158-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048382071"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ejor.2011.09.023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050149320"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/opre.1120.1048", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064726603"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/opre.1120.1153", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064726708"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/opre.50.3.415.7751", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064731530"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/trsc.1030.0056", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064734095"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/trsc.1030.0057", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064734096"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/trsc.1110.0368", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064734418"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/trsc.1110.0399", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064734448"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/trsc.2013.0500", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064734846"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/trsc.23.3.166", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064735132"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-11", 
    "datePublishedReg": "2017-11-01", 
    "description": "This paper addresses the two-echelon capacitated vehicle routing problem (2E-CVRP) with stochastic demands (2E-CVRPSD) in city logistics. A stochastic program with recourse is used to describe the problem. This program aims to minimize the sum of the travel cost and the expected cost of recourse actions resulting from potential route failures. In a two-echelon distribution system, split deliveries are allowed at the first level but not at the second level, thereby increasing the difficulty of calculating the expected failure cost. Three types of routes with or without split deliveries are identified. Different methods are devised or adapted from the literature to compute the failure cost. A genetic-algorithm-based (GA) approach is proposed to solve the 2E-CVRPSD. A simple encoding and decoding scheme, a modified route copy crossover operator, and a satellite-selection-based mutation operator are devised in this approach. The numerical results show that for all instances, the expected cost of the best 2E-CVRPSD solution found by the proposed approach is not greater than that of the best-known 2E-CVRP solution with an average relative gap of 2.57%. Therefore, the GA-based approach can find high-quality solutions for the 2E-CVRPSD.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1057/s41274-016-0170-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1087747", 
        "issn": [
          "0160-5682", 
          "1476-9360"
        ], 
        "name": "Journal of the Operational Research Society", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "11", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "68"
      }
    ], 
    "name": "A genetic-algorithm-based approach to the two-echelon capacitated vehicle routing problem with stochastic demands in logistics service", 
    "pagination": "1409-1421", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "6ed194635411b0e30af80960de71b6110274f37d636bcaf7975a91f1859e63b0"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1057/s41274-016-0170-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1074200968"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1057/s41274-016-0170-7", 
      "https://app.dimensions.ai/details/publication/pub.1074200968"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T17:30", 
    "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_8672_00000508.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1057/s41274-016-0170-7"
  }
]
 

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/s41274-016-0170-7'

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/s41274-016-0170-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1057/s41274-016-0170-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1057/s41274-016-0170-7'


 

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

178 TRIPLES      21 PREDICATES      57 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1057/s41274-016-0170-7 schema:about anzsrc-for:01
2 anzsrc-for:0104
3 schema:author Necb3538154c842dd93656de319736342
4 schema:citation sg:pub.10.1007/978-1-4614-6322-1_7
5 sg:pub.10.1007/978-3-642-20364-0_16
6 sg:pub.10.1007/s10852-005-9033-y
7 sg:pub.10.1007/s11067-013-9190-x
8 sg:pub.10.1007/s11590-012-0568-3
9 sg:pub.10.1057/jors.2014.88
10 sg:pub.10.1057/jors.2015.19
11 https://doi.org/10.1016/0377-2217(80)90124-1
12 https://doi.org/10.1016/j.asoc.2013.01.007
13 https://doi.org/10.1016/j.cor.2012.04.007
14 https://doi.org/10.1016/j.cor.2012.10.016
15 https://doi.org/10.1016/j.cor.2014.06.008
16 https://doi.org/10.1016/j.cor.2014.07.011
17 https://doi.org/10.1016/j.ejor.2011.09.023
18 https://doi.org/10.1016/j.endm.2010.05.081
19 https://doi.org/10.1016/j.ijpe.2010.01.013
20 https://doi.org/10.1016/j.orl.2006.12.009
21 https://doi.org/10.1016/s0305-0548(03)00158-8
22 https://doi.org/10.1080/00207543.2011.622310
23 https://doi.org/10.1080/0305215x.2014.928818
24 https://doi.org/10.1155/2014/517467
25 https://doi.org/10.1287/opre.1120.1048
26 https://doi.org/10.1287/opre.1120.1153
27 https://doi.org/10.1287/opre.50.3.415.7751
28 https://doi.org/10.1287/trsc.1030.0056
29 https://doi.org/10.1287/trsc.1030.0057
30 https://doi.org/10.1287/trsc.1110.0368
31 https://doi.org/10.1287/trsc.1110.0399
32 https://doi.org/10.1287/trsc.2013.0500
33 https://doi.org/10.1287/trsc.23.3.166
34 schema:datePublished 2017-11
35 schema:datePublishedReg 2017-11-01
36 schema:description This paper addresses the two-echelon capacitated vehicle routing problem (2E-CVRP) with stochastic demands (2E-CVRPSD) in city logistics. A stochastic program with recourse is used to describe the problem. This program aims to minimize the sum of the travel cost and the expected cost of recourse actions resulting from potential route failures. In a two-echelon distribution system, split deliveries are allowed at the first level but not at the second level, thereby increasing the difficulty of calculating the expected failure cost. Three types of routes with or without split deliveries are identified. Different methods are devised or adapted from the literature to compute the failure cost. A genetic-algorithm-based (GA) approach is proposed to solve the 2E-CVRPSD. A simple encoding and decoding scheme, a modified route copy crossover operator, and a satellite-selection-based mutation operator are devised in this approach. The numerical results show that for all instances, the expected cost of the best 2E-CVRPSD solution found by the proposed approach is not greater than that of the best-known 2E-CVRP solution with an average relative gap of 2.57%. Therefore, the GA-based approach can find high-quality solutions for the 2E-CVRPSD.
37 schema:genre research_article
38 schema:inLanguage en
39 schema:isAccessibleForFree false
40 schema:isPartOf N0dbd167a19274d0b87f5743372d18ac7
41 Ne7aab3d36d7c47808fba9a7789db5c36
42 sg:journal.1087747
43 schema:name A genetic-algorithm-based approach to the two-echelon capacitated vehicle routing problem with stochastic demands in logistics service
44 schema:pagination 1409-1421
45 schema:productId N322ac61fe28c40e68e2eed42a620072e
46 N724f7d66ff27433592f01fa199e51adf
47 N7f3aecb1bc4a47d288c5979e36e6a638
48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074200968
49 https://doi.org/10.1057/s41274-016-0170-7
50 schema:sdDatePublished 2019-04-10T17:30
51 schema:sdLicense https://scigraph.springernature.com/explorer/license/
52 schema:sdPublisher Ne300aa568ede4ce6ae376655050c856d
53 schema:url http://link.springer.com/10.1057/s41274-016-0170-7
54 sgo:license sg:explorer/license/
55 sgo:sdDataset articles
56 rdf:type schema:ScholarlyArticle
57 N0dbd167a19274d0b87f5743372d18ac7 schema:issueNumber 11
58 rdf:type schema:PublicationIssue
59 N2c97411e7dac42e7b98f1ea8c512947c rdf:first sg:person.012446563503.49
60 rdf:rest rdf:nil
61 N322ac61fe28c40e68e2eed42a620072e schema:name doi
62 schema:value 10.1057/s41274-016-0170-7
63 rdf:type schema:PropertyValue
64 N724f7d66ff27433592f01fa199e51adf schema:name dimensions_id
65 schema:value pub.1074200968
66 rdf:type schema:PropertyValue
67 N7f3aecb1bc4a47d288c5979e36e6a638 schema:name readcube_id
68 schema:value 6ed194635411b0e30af80960de71b6110274f37d636bcaf7975a91f1859e63b0
69 rdf:type schema:PropertyValue
70 Nb175545da6574c4198d3ee131acdfa54 rdf:first sg:person.013206644677.93
71 rdf:rest N2c97411e7dac42e7b98f1ea8c512947c
72 Ne300aa568ede4ce6ae376655050c856d schema:name Springer Nature - SN SciGraph project
73 rdf:type schema:Organization
74 Ne7aab3d36d7c47808fba9a7789db5c36 schema:volumeNumber 68
75 rdf:type schema:PublicationVolume
76 Necb3538154c842dd93656de319736342 rdf:first sg:person.010615416167.17
77 rdf:rest Nb175545da6574c4198d3ee131acdfa54
78 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
79 schema:name Mathematical Sciences
80 rdf:type schema:DefinedTerm
81 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
82 schema:name Statistics
83 rdf:type schema:DefinedTerm
84 sg:journal.1087747 schema:issn 0160-5682
85 1476-9360
86 schema:name Journal of the Operational Research Society
87 rdf:type schema:Periodical
88 sg:person.010615416167.17 schema:affiliation https://www.grid.ac/institutes/grid.32566.34
89 schema:familyName Wang
90 schema:givenName Kangzhou
91 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010615416167.17
92 rdf:type schema:Person
93 sg:person.012446563503.49 schema:affiliation https://www.grid.ac/institutes/grid.443284.d
94 schema:familyName Zhao
95 schema:givenName Yingxue
96 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012446563503.49
97 rdf:type schema:Person
98 sg:person.013206644677.93 schema:affiliation https://www.grid.ac/institutes/grid.194645.b
99 schema:familyName Lan
100 schema:givenName Shulin
101 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013206644677.93
102 rdf:type schema:Person
103 sg:pub.10.1007/978-1-4614-6322-1_7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008057272
104 https://doi.org/10.1007/978-1-4614-6322-1_7
105 rdf:type schema:CreativeWork
106 sg:pub.10.1007/978-3-642-20364-0_16 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030173503
107 https://doi.org/10.1007/978-3-642-20364-0_16
108 rdf:type schema:CreativeWork
109 sg:pub.10.1007/s10852-005-9033-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1011557734
110 https://doi.org/10.1007/s10852-005-9033-y
111 rdf:type schema:CreativeWork
112 sg:pub.10.1007/s11067-013-9190-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1039454786
113 https://doi.org/10.1007/s11067-013-9190-x
114 rdf:type schema:CreativeWork
115 sg:pub.10.1007/s11590-012-0568-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035853361
116 https://doi.org/10.1007/s11590-012-0568-3
117 rdf:type schema:CreativeWork
118 sg:pub.10.1057/jors.2014.88 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021669263
119 https://doi.org/10.1057/jors.2014.88
120 rdf:type schema:CreativeWork
121 sg:pub.10.1057/jors.2015.19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005684925
122 https://doi.org/10.1057/jors.2015.19
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/0377-2217(80)90124-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015061066
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/j.asoc.2013.01.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005128741
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/j.cor.2012.04.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031623177
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/j.cor.2012.10.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026845388
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/j.cor.2014.06.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037802915
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/j.cor.2014.07.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010267688
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/j.ejor.2011.09.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050149320
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1016/j.endm.2010.05.081 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017979035
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1016/j.ijpe.2010.01.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000461499
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1016/j.orl.2006.12.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034668731
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1016/s0305-0548(03)00158-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048382071
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1080/00207543.2011.622310 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002129394
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1080/0305215x.2014.928818 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036727453
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1155/2014/517467 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046171756
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1287/opre.1120.1048 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064726603
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1287/opre.1120.1153 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064726708
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1287/opre.50.3.415.7751 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064731530
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1287/trsc.1030.0056 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064734095
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1287/trsc.1030.0057 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064734096
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1287/trsc.1110.0368 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064734418
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1287/trsc.1110.0399 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064734448
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1287/trsc.2013.0500 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064734846
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1287/trsc.23.3.166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064735132
169 rdf:type schema:CreativeWork
170 https://www.grid.ac/institutes/grid.194645.b schema:alternateName University of Hong Kong
171 schema:name Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China
172 rdf:type schema:Organization
173 https://www.grid.ac/institutes/grid.32566.34 schema:alternateName Lanzhou University
174 schema:name School of Management, Lanzhou University, Lanzhou, China
175 rdf:type schema:Organization
176 https://www.grid.ac/institutes/grid.443284.d schema:alternateName University of International Business and Economics
177 schema:name School of International Trade and Economics, University of International Business and Economics, Beijing, China
178 rdf:type schema:Organization
 




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


...