Variable neighborhood search based approaches to a vehicle scheduling problem in agriculture

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 mixe...

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Bibliographic Details
Published in:International transactions in operational research Vol. 27; no. 1; pp. 26 - 56
Main Authors: Anokić, Ana, Stanimirović, Zorica, Davidović, Tatjana, Stakić, Đorđe
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.01.2020
Subjects:
Constraints
Heuristic methods
Linear programming
metaheuristics
Mixed integer
mixed integer quadratically constrained programming
Operations research
Production scheduling
Scheduling
transportation of agriculture raw materials
variable neighborhood search
vehicle scheduling problem
ISSN:0969-6016, 1475-3995
Online Access:Get full text
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Summary: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.
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ISSN:0969-6016
1475-3995
DOI:10.1111/itor.12480