|Affiliations:||Mathematical Institute of the Serbian Academy of Sciences and Arts||Title:||Variable neighborhood search based approaches to a vehicle scheduling problem in agriculture||Journal:||International Transactions in Operational Research||Volume:||27||Issue:||1||First page:||26||Last page:||56||Issue Date:||1-Jan-2020||Rank:||M21||ISSN:||0969-6016||DOI:||10.1111/itor.12480||Abstract:||
A vehicle scheduling problem (VSP) that arises from sugar beet transportation within minimum working time under the set of constraints reflecting a real-life situation is considered. A mixed integer quadratically constrained programming (MIQCP) model of the considered VSP and reformulation to a mixed integer linear program (MILP) are proposed and used within the framework of Lingo 17 solver, producing optimal solutions only for small-sized problem instances. Two variants of the variable neighborhood search (VNS) metaheuristic—basic VNS (BVNS) and skewed VNS (SVNS) are designed to efficiently deal with large-sized problem instances. The proposed VNS approaches are evaluated and compared against Lingo 17 and each other on the set of real-life and generated problem instances. Computational results show that both BVNS and SVNS reach all known optimal solutions on small-sized instances and are comparable on medium- and large-sized instances. In general, SVNS significantly outperforms BVNS in terms of running times.
|Keywords:||metaheuristics | mixed integer quadratically constrained programming | transportation of agriculture raw materials | variable neighborhood search | vehicle scheduling problem||Publisher:||Wiley||Project:||Graph theory and mathematical programming with applications in chemistry and computer science
Mathematical Modelas and Optimization Methods on Large-Scale Systems
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