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  <titleInfo>
    <title>Adaptive variable neighborhood search algorithms for solving capacitated vehicle routing problems</title>
  </titleInfo>
  <name type="personal">
    <namePart>Sikarin Vinyoopradit</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Voratas Kachitvichyanukul</namePart>
    <role>
      <roleTerm type="text">Chairperson</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Huynh, Trung Luong</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Pisut Koomsap</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
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  <originInfo>
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      <placeTerm type="code" authority="marccountry">th</placeTerm>
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    <place>
      <placeTerm type="text">Pathum Thani</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>2012</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <extent>104 p. : ill. (some col.), charts</extent>
  </physicalDescription>
  <abstract>This  research  presents  adaptive  variable  neighborhood  search  algorithms  for  solving Capacitated  Vehicle  Routing  Problems  (CVRP).  Four  Variable  Neighborhood  Search (VNS)  based  algorithms  to  optimize  Capacitated  Vehicle  Routing  Problems  (CVRP)  are studied.  The  first  algorithm  is  a  Variable  Neighborhood  Search  (VNS)  integrated  with Tabu Search (TS) implemented with new proposed Tabu List. The second algorithm is an Adaptive  Variable  Neighborhood  Search  (AVNS)  algorithm  to  improve  the  perturbation process of VNS algorithm by allowing the frequently used sequences in local optimum to be  selected  via  integrating  Roulette  Wheel  Selection  method.  The  third  algorithm  is  an alternative  AVNS  algorithm  that  adopts  approach  similar  to  Ant  Colony  Optimization (ACO) to the AVNS algorithm called A-AVNS1 to reduce the influence of the infrequent used sequences. An Adaptive Roulette Wheel Selection method is proposed in A-AVNS2 algorithm to improve algorithm exploration efficiency. Numerical experiments are carried out  using  the  published  benchmark  test  problems.  The  results  indicated  that  the  proposed adaptive  VNS  algorithms  improved  solution  quality  and  solution  time  for  large  problem sizes.</abstract>
  <note>Submitted in partial fulfillment of the requirements for the  degree of Master of Engineering in Industrial and Manufacturing Engineering, School of Engineering and Technology</note>
  <note>Thesis (M. Eng.) - Asian Institute of Technology, 2012</note>
  <subject authority="lcsh">
    <topic>Vehicle routing problem</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Algorithms</topic>
  </subject>
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    <titleInfo>
      <title>Thesis ; no. ISE-12-51</title>
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    <name type="corporate">
      <namePart>Asian Institute of Technology.</namePart>
      <namePart/>
    </name>
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  <identifier type="uri">http://203.159.5.9/ait-thesis/detail.php?q=B03378 </identifier>
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