A mathematical model for the route optimization of service vehicles

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Published Apr 12, 2017
DOI https://doi.org/10.18844/gjbem.v7i1.1410

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İlker Küçükoğlu
Uludag University, Faculty of Engineering, Industrial Engineering Department, Bursa, 16059, Turkey * ADDRESS FOR CORRESPONDENCE: İlker Küçükoğlu, Uludag University, Faculty of Engineering, Industrial Engineering Department, Bursa, 16059, Turkey E-mail address: [email protected] / Tel.: +90-224-294-2091
Dilara Zümbülova
Uludag University, Faculty of Engineering, Industrial Engineering Department, Bursa, 16059, Turkey
Koray Reyhan
Uludag University, Faculty of Engineering, Industrial Engineering Department, Bursa, 16059, Turkey
Salih Görgülü
Uludag University, Faculty of Engineering, Industrial Engineering Department, Bursa, 16059, Turkey
Nursel Öztürk
Uludag University, Faculty of Engineering, Industrial Engineering Department, Bursa, 16059, Turkey

Abstract

The route planning of service vehicles is an important issue for large-scale enterprises which have hundreds of employee. Especially for the flexible shift system which brings about uncertainty for the drivers, the route plans have to be formed daily by the managers. This study addresses the route optimization problem of an automotive company which aims to minimize total transportation cost of the service fleet and proposes a mixed integer mathematical model to solve problem. The objective of the mathematical model is to minimize fixed and transportation cost of the fleet by considering vehicle capacities and travelling time constraints. The mathematical model is tested on a randomly generated problem set which consist of different sized instances for homogeneous service fleet. The computational results obtained by the Gurobi solver show that the proposed mathematical model is capable to find route plans for the real-life service vehicles routing decisions that can minimize total transportation cost of the fleet.

 

Keywords: Vehicle routing, service systems, mathematical modelling;

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Article Details

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Vol 7 No 1 (2017): March
Section
Articles
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