
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/">
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:title xml:lang="eng">Metaheuristic approaches to a vehicle scheduling problem in sugar beet transportation</dc:title>
  <dc:identifier>https://phaidrabg.bg.ac.rs/o:29591</dc:identifier>
  <dc:identifier>doi:10.1007/s12351-019-00495-z</dc:identifier>
  <dc:identifier>ISSN: 1109-2858</dc:identifier>
  <dc:source>Operational research 21(3)</dc:source>
  <dc:subject xml:lang="eng">Keywords: Optimization in transport, Vehicle scheduling problem, Mixed integer linear programming, Variable neighborhood search, Greedy Randomized Adaptive Search Procedure</dc:subject>
  <dc:rights>All rights reserved</dc:rights>
  <dc:creator id="https://orcid.org/0000-0002-9159-3491">Anokić, Ana</dc:creator>
  <dc:creator id="https://orcid.org/0000-0001-5658-4111">Stanimirović, Zorica</dc:creator>
  <dc:creator id="https://orcid.org/0000-0002-3241-4289 https://plus.cobiss.net/cobiss/sr/sr/conor/27797863">Stakić, Đorđe</dc:creator>
  <dc:creator id="https://orcid.org/0000-0001-9561-5339">Davidović, Tatjana</dc:creator>
  <dc:format>application/pdf</dc:format>
  <dc:format>2971462 bytes</dc:format>
  <dc:date>2021</dc:date>
  <dc:language>eng</dc:language>
  <dc:description xml:lang="eng">Abstract:
A variant of vehicle scheduling problem (VSP) arising from the sugar beet transportation in a sugar factory in Serbia is introduced. The objective of the considered VSP
is to minimize the required transportation time under problem-specific constraints.
The problem is formulated as a mixed integer linear program (MILP). Within the
framework of commercial CPLEX solver the proposed MILP model was able to produce optimal solutions for small size problem instances. Therefore, two metaheuristic methods, variable neighborhood search (VNS) and greedy randomized adaptive search procedure (GRASP), are designed to solve problem instances of larger
dimensions. The proposed GRASP and VNS are evaluated and compared against
CPLEX and each other on the set of real-life and generated problem instances. Computational results show that VNS is superior method with respect to the solution
quality, while GRASP is able to find high quality solutions within very short running times.</dc:description>
  <dc:description xml:lang="eng">The authors also state that the research conducted in this paper was partially supported by Serbian Ministry of Education, Science and Technological Development under the Grants Nos. 174010 and 174033.</dc:description>
</oai_dc:dc>
