A petrol station replenishment problem: new variant and formulation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

Abdelaziz Benantar, Rachid Ouafi, Jaouad Boukachour

ABSTRACT

One of the most important problems in the petroleum industry is the well-known petrol station replenishment problem with time windows, which calls for the determination of optimal routes by using a fleet of tank trucks to serve a set of petrol stations over a given planning horizon. In this paper, we introduce a model and solve a specific problem that originates from a real-life application arising in the fuel distribution where specific attention is paid to tank trucks with compartments and customers with different types of products and time windows. Literally, we call the resulting problem the multi-compartment vehicle routing problem with time windows (MCVRPTW). To solve the MCVRPTW, we begin by describing the problem, providing its mathematical formulation and discussing the sense of its constraints. As the problem is NP-hard, we propose an efficient tabu search algorithm for its solution. We introduce the Kolmogorov–Smirnov statistic into the framework of the tabu search to manage the neighbourhood size. We evaluate the performance of the algorithm on a set of vehicle routing problems with time windows instances as well as other realistic instances. Our results are compared to CPLEX, to the heuristics reported in the literature and also to those extracted from the company plans. More... »

PAGES

6

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12159-016-0133-z

DOI

http://dx.doi.org/10.1007/s12159-016-0133-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1035866773


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/2008/0802", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Computation Theory and Mathematics", 
        "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": {
          "name": [
            "Department of Operational Research, USTHB University, P.O. Box 32, 16111, Bab-Ezzouar, Algeria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Benantar", 
        "givenName": "Abdelaziz", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Operational Research, USTHB University, P.O. Box 32, 16111, Bab-Ezzouar, Algeria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ouafi", 
        "givenName": "Rachid", 
        "id": "sg:person.015651474676.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015651474676.07"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "LMAH, Normandie University, ULH, 76600, Le Havre, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Boukachour", 
        "givenName": "Jaouad", 
        "id": "sg:person.010424432511.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010424432511.42"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/0377-2217(94)00189-j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001669190"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cor.2009.06.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004316199"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0952-1976(02)00011-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005960658"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.omega.2006.11.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005965537"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ejor.2012.02.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007250271"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10589-005-3070-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011587819", 
          "https://doi.org/10.1007/s10589-005-3070-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10589-005-3070-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011587819", 
          "https://doi.org/10.1007/s10589-005-3070-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1012335604", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4615-6089-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012335604", 
          "https://doi.org/10.1007/978-1-4615-6089-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4615-6089-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012335604", 
          "https://doi.org/10.1007/978-1-4615-6089-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0377-2217(02)00363-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013201704"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0377-2217(02)00363-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013201704"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1057/palgrave.jors.2602374", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022236138", 
          "https://doi.org/10.1057/palgrave.jors.2602374"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ejor.2007.08.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023433686"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cor.2006.10.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026361638"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1018940026670", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032595641", 
          "https://doi.org/10.1023/a:1018940026670"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0377-2217(02)00676-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034971145"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0377-2217(02)00676-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034971145"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0305-0548(03)00163-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037265944"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0305-0548(03)00163-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037265944"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ejor.2009.05.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040085565"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0305-0483(96)00059-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040960849"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijpe.2013.04.034", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042478075"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2012.05.064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044437294"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1057/palgrave.jors.2601163", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044607419", 
          "https://doi.org/10.1057/palgrave.jors.2601163"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1057/palgrave.jors.2602464", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045030380", 
          "https://doi.org/10.1057/palgrave.jors.2602464"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cor.2012.07.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052688743"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02579017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053004335", 
          "https://doi.org/10.1007/bf02579017"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02579017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053004335", 
          "https://doi.org/10.1007/bf02579017"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cor.2007.11.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053570178"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/ijoc.15.4.333.24890", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064707112"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/ijoc.9.4.417", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064707647"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/inte.17.1.107", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064708995"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/inte.25.2.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064709892"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/mnsc.27.1.19", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064719377"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/opre.35.2.254", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064729808"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/opre.43.3.379", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064730760"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/trsc.31.2.170", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064735431"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cec.2001.934457", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094108010"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icsmc.2002.1168021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094230789"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/1.9781611973594", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1108604374"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-12", 
    "datePublishedReg": "2016-12-01", 
    "description": "One of the most important problems in the petroleum industry is the well-known petrol station replenishment problem with time windows, which calls for the determination of optimal routes by using a fleet of tank trucks to serve a set of petrol stations over a given planning horizon. In this paper, we introduce a model and solve a specific problem that originates from a real-life application arising in the fuel distribution where specific attention is paid to tank trucks with compartments and customers with different types of products and time windows. Literally, we call the resulting problem the multi-compartment vehicle routing problem with time windows (MCVRPTW). To solve the MCVRPTW, we begin by describing the problem, providing its mathematical formulation and discussing the sense of its constraints. As the problem is NP-hard, we propose an efficient tabu search algorithm for its solution. We introduce the Kolmogorov\u2013Smirnov statistic into the framework of the tabu search to manage the neighbourhood size. We evaluate the performance of the algorithm on a set of vehicle routing problems with time windows instances as well as other realistic instances. Our results are compared to CPLEX, to the heuristics reported in the literature and also to those extracted from the company plans.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s12159-016-0133-z", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1136819", 
        "issn": [
          "1865-035X", 
          "1865-0368"
        ], 
        "name": "Logistics Research", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "9"
      }
    ], 
    "name": "A petrol station replenishment problem: new variant and formulation", 
    "pagination": "6", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "aadb9a96dbac3f447763eece6d974eaf9ce6d59446563628be37f135e1492820"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12159-016-0133-z"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1035866773"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12159-016-0133-z", 
      "https://app.dimensions.ai/details/publication/pub.1035866773"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:08", 
    "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/v90/0000000367_0000000367/records_88230_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs12159-016-0133-z"
  }
]
 

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/s12159-016-0133-z'

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/s12159-016-0133-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12159-016-0133-z'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12159-016-0133-z'


 

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

188 TRIPLES      21 PREDICATES      62 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12159-016-0133-z schema:about anzsrc-for:08
2 anzsrc-for:0802
3 schema:author N410b72d673a34534a20a8f10cbb772d1
4 schema:citation sg:pub.10.1007/978-1-4615-6089-0
5 sg:pub.10.1007/bf02579017
6 sg:pub.10.1007/s10589-005-3070-3
7 sg:pub.10.1023/a:1018940026670
8 sg:pub.10.1057/palgrave.jors.2601163
9 sg:pub.10.1057/palgrave.jors.2602374
10 sg:pub.10.1057/palgrave.jors.2602464
11 https://app.dimensions.ai/details/publication/pub.1012335604
12 https://doi.org/10.1016/0377-2217(94)00189-j
13 https://doi.org/10.1016/j.cor.2006.10.006
14 https://doi.org/10.1016/j.cor.2007.11.007
15 https://doi.org/10.1016/j.cor.2009.06.022
16 https://doi.org/10.1016/j.cor.2012.07.018
17 https://doi.org/10.1016/j.ejor.2007.08.016
18 https://doi.org/10.1016/j.ejor.2009.05.008
19 https://doi.org/10.1016/j.ejor.2012.02.007
20 https://doi.org/10.1016/j.eswa.2012.05.064
21 https://doi.org/10.1016/j.ijpe.2013.04.034
22 https://doi.org/10.1016/j.omega.2006.11.007
23 https://doi.org/10.1016/s0305-0483(96)00059-x
24 https://doi.org/10.1016/s0305-0548(03)00163-1
25 https://doi.org/10.1016/s0377-2217(02)00363-6
26 https://doi.org/10.1016/s0377-2217(02)00676-8
27 https://doi.org/10.1016/s0952-1976(02)00011-8
28 https://doi.org/10.1109/cec.2001.934457
29 https://doi.org/10.1109/icsmc.2002.1168021
30 https://doi.org/10.1137/1.9781611973594
31 https://doi.org/10.1287/ijoc.15.4.333.24890
32 https://doi.org/10.1287/ijoc.9.4.417
33 https://doi.org/10.1287/inte.17.1.107
34 https://doi.org/10.1287/inte.25.2.1
35 https://doi.org/10.1287/mnsc.27.1.19
36 https://doi.org/10.1287/opre.35.2.254
37 https://doi.org/10.1287/opre.43.3.379
38 https://doi.org/10.1287/trsc.31.2.170
39 schema:datePublished 2016-12
40 schema:datePublishedReg 2016-12-01
41 schema:description One of the most important problems in the petroleum industry is the well-known petrol station replenishment problem with time windows, which calls for the determination of optimal routes by using a fleet of tank trucks to serve a set of petrol stations over a given planning horizon. In this paper, we introduce a model and solve a specific problem that originates from a real-life application arising in the fuel distribution where specific attention is paid to tank trucks with compartments and customers with different types of products and time windows. Literally, we call the resulting problem the multi-compartment vehicle routing problem with time windows (MCVRPTW). To solve the MCVRPTW, we begin by describing the problem, providing its mathematical formulation and discussing the sense of its constraints. As the problem is NP-hard, we propose an efficient tabu search algorithm for its solution. We introduce the Kolmogorov–Smirnov statistic into the framework of the tabu search to manage the neighbourhood size. We evaluate the performance of the algorithm on a set of vehicle routing problems with time windows instances as well as other realistic instances. Our results are compared to CPLEX, to the heuristics reported in the literature and also to those extracted from the company plans.
42 schema:genre research_article
43 schema:inLanguage en
44 schema:isAccessibleForFree true
45 schema:isPartOf N08ae194d0bc04814b5f56d6e540f5523
46 N39017d492afe4b95b54a049086d6cd62
47 sg:journal.1136819
48 schema:name A petrol station replenishment problem: new variant and formulation
49 schema:pagination 6
50 schema:productId N493488875d414ea3a975650192508c44
51 N4f0e57403d6c4042ba993790120b11b9
52 Nebddc25f39794cb8a5a9fce456531cb6
53 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035866773
54 https://doi.org/10.1007/s12159-016-0133-z
55 schema:sdDatePublished 2019-04-11T13:08
56 schema:sdLicense https://scigraph.springernature.com/explorer/license/
57 schema:sdPublisher N5616b7e03cc24a92be686214ec6b1b54
58 schema:url http://link.springer.com/10.1007%2Fs12159-016-0133-z
59 sgo:license sg:explorer/license/
60 sgo:sdDataset articles
61 rdf:type schema:ScholarlyArticle
62 N0297b65bf8624c049b7737c83befd1ef schema:name Department of Operational Research, USTHB University, P.O. Box 32, 16111, Bab-Ezzouar, Algeria
63 rdf:type schema:Organization
64 N08ae194d0bc04814b5f56d6e540f5523 schema:volumeNumber 9
65 rdf:type schema:PublicationVolume
66 N39017d492afe4b95b54a049086d6cd62 schema:issueNumber 1
67 rdf:type schema:PublicationIssue
68 N410b72d673a34534a20a8f10cbb772d1 rdf:first N8d6d0ead481f4c028653e7ae5c377457
69 rdf:rest Nf8a7f40c81f945e683f0bf5da9644ebe
70 N493488875d414ea3a975650192508c44 schema:name dimensions_id
71 schema:value pub.1035866773
72 rdf:type schema:PropertyValue
73 N4f0e57403d6c4042ba993790120b11b9 schema:name doi
74 schema:value 10.1007/s12159-016-0133-z
75 rdf:type schema:PropertyValue
76 N5616b7e03cc24a92be686214ec6b1b54 schema:name Springer Nature - SN SciGraph project
77 rdf:type schema:Organization
78 N75bcf1230cbb4f61840370f6dccd37a2 schema:name LMAH, Normandie University, ULH, 76600, Le Havre, France
79 rdf:type schema:Organization
80 N82207400982246f38cb8a70933d4f3d5 rdf:first sg:person.010424432511.42
81 rdf:rest rdf:nil
82 N8d6d0ead481f4c028653e7ae5c377457 schema:affiliation Ne9723ceb4d5d48f2b6ac28867621352e
83 schema:familyName Benantar
84 schema:givenName Abdelaziz
85 rdf:type schema:Person
86 Ne9723ceb4d5d48f2b6ac28867621352e schema:name Department of Operational Research, USTHB University, P.O. Box 32, 16111, Bab-Ezzouar, Algeria
87 rdf:type schema:Organization
88 Nebddc25f39794cb8a5a9fce456531cb6 schema:name readcube_id
89 schema:value aadb9a96dbac3f447763eece6d974eaf9ce6d59446563628be37f135e1492820
90 rdf:type schema:PropertyValue
91 Nf8a7f40c81f945e683f0bf5da9644ebe rdf:first sg:person.015651474676.07
92 rdf:rest N82207400982246f38cb8a70933d4f3d5
93 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
94 schema:name Information and Computing Sciences
95 rdf:type schema:DefinedTerm
96 anzsrc-for:0802 schema:inDefinedTermSet anzsrc-for:
97 schema:name Computation Theory and Mathematics
98 rdf:type schema:DefinedTerm
99 sg:journal.1136819 schema:issn 1865-035X
100 1865-0368
101 schema:name Logistics Research
102 rdf:type schema:Periodical
103 sg:person.010424432511.42 schema:affiliation N75bcf1230cbb4f61840370f6dccd37a2
104 schema:familyName Boukachour
105 schema:givenName Jaouad
106 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010424432511.42
107 rdf:type schema:Person
108 sg:person.015651474676.07 schema:affiliation N0297b65bf8624c049b7737c83befd1ef
109 schema:familyName Ouafi
110 schema:givenName Rachid
111 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015651474676.07
112 rdf:type schema:Person
113 sg:pub.10.1007/978-1-4615-6089-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012335604
114 https://doi.org/10.1007/978-1-4615-6089-0
115 rdf:type schema:CreativeWork
116 sg:pub.10.1007/bf02579017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053004335
117 https://doi.org/10.1007/bf02579017
118 rdf:type schema:CreativeWork
119 sg:pub.10.1007/s10589-005-3070-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011587819
120 https://doi.org/10.1007/s10589-005-3070-3
121 rdf:type schema:CreativeWork
122 sg:pub.10.1023/a:1018940026670 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032595641
123 https://doi.org/10.1023/a:1018940026670
124 rdf:type schema:CreativeWork
125 sg:pub.10.1057/palgrave.jors.2601163 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044607419
126 https://doi.org/10.1057/palgrave.jors.2601163
127 rdf:type schema:CreativeWork
128 sg:pub.10.1057/palgrave.jors.2602374 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022236138
129 https://doi.org/10.1057/palgrave.jors.2602374
130 rdf:type schema:CreativeWork
131 sg:pub.10.1057/palgrave.jors.2602464 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045030380
132 https://doi.org/10.1057/palgrave.jors.2602464
133 rdf:type schema:CreativeWork
134 https://app.dimensions.ai/details/publication/pub.1012335604 schema:CreativeWork
135 https://doi.org/10.1016/0377-2217(94)00189-j schema:sameAs https://app.dimensions.ai/details/publication/pub.1001669190
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/j.cor.2006.10.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026361638
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/j.cor.2007.11.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053570178
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/j.cor.2009.06.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004316199
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.cor.2012.07.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052688743
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/j.ejor.2007.08.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023433686
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/j.ejor.2009.05.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040085565
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/j.ejor.2012.02.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007250271
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1016/j.eswa.2012.05.064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044437294
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1016/j.ijpe.2013.04.034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042478075
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1016/j.omega.2006.11.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005965537
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1016/s0305-0483(96)00059-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1040960849
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1016/s0305-0548(03)00163-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037265944
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1016/s0377-2217(02)00363-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013201704
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1016/s0377-2217(02)00676-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034971145
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/s0952-1976(02)00011-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005960658
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1109/cec.2001.934457 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094108010
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1109/icsmc.2002.1168021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094230789
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1137/1.9781611973594 schema:sameAs https://app.dimensions.ai/details/publication/pub.1108604374
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1287/ijoc.15.4.333.24890 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064707112
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1287/ijoc.9.4.417 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064707647
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1287/inte.17.1.107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064708995
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1287/inte.25.2.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064709892
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1287/mnsc.27.1.19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064719377
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1287/opre.35.2.254 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064729808
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1287/opre.43.3.379 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064730760
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1287/trsc.31.2.170 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064735431
188 rdf:type schema:CreativeWork
 




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


...