Authors: Stanimirović, Zorica
Stakić, Đorđe
Davidović, Tatjana 
Anokić, Ana
Title: General Variable Neighborhood Search for Scheduling Heterogeneous Vehicles in Agriculture
Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume: 11328 LNCS
First page: 125
Last page: 140
Conference: 6th International Conference on Variable Neighborhood Search, ICVNS 2018; Sithonia; Greece; 4 October 2018 through 7 October 2018
Issue Date: 1-Jan-2019
ISBN: 978-3-030-15842-2
ISSN: 0302-9743
DOI: 10.1007/978-3-030-15843-9_11
A new variant of Vehicle Scheduling Problem (VSP), denoted as Vehicle Scheduling Problem with Heterogeneous Vehicles (VSP-HV), which arises from optimizing the sugar beet transportation in a sugar factory in Serbia is introduced. The objective of the considered VSP-HV is to minimize the time required for daily transportation of sugar beet by heterogeneous vehicles under problem-specific constraints. General Variable Neighborhood Search (GVNS) is designed as a solution method for the considered problem. A computational study is conducted on the set of real-life instances, as well as on the set of generated instances of larger dimensions. A Mixed Integer Quadratically Constraint Programming (MIQCP) model is developed and used within commercial Lingo 17 solver to obtain optimal or feasible solutions for small-size real-life problem instances. Experimental results show that the proposed GVNS quickly reaches all known optimal solutions or improves the upper bounds of feasible solutions on small-size instances. On larger problem instances, for which Lingo 17 could not find feasible solutions, GVNS provided its best solutions for limited CPU time.
Keywords: Vehicle scheduling problem | Heterogeneous vehicles | Single depot | Transportation in agriculture | Variable neighborhood search
Publisher: Springer Link
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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