Solving Capacitated Location Routing Problem by Variable Neighborhood Descent and GA-Artificial Neural Network Hybrid Method

  • Engin Pekel Yildiz Technical University
  • Selin Soner Kara Yildiz Technical University
DOI: https://doi.org/10.7307/ptt.v30i5.2640
Keywords: artificial neural network, capacitated location-routing problem, genetic algorithm, heuristics, k-nearest neighborhood, variable neighborhood descent

Abstract

This paper aims to find the optimal depot locations and vehicle routings for spare parts of an automotive company considering future demands. The capacitated location-routing problem (CLRP), which has been practiced by various methods, is performed to find the optimal depot locations and routings by additionally using the artificial neural network (ANN). A novel multi-stage approach, which is performed to lower transportation cost, is carried out in CLRP. Initially, important factors for customer demand are tested with an univariate analysis and used as inputs in the prediction step. Then, genetic algorithm (GA) and ANN are hybridized and applied to provide future demands. The location of depots and the routings of the vehicles are determined by using the variable neighborhood descent (VND) algorithm. Five neighborhood structures, which are either routing or location type, are implemented in both shaking and local search steps. GA-ANN and VND are applied in the related steps successfully. Thanks to the performed VND algorithm, the company lowers its transportation cost by 2.35% for the current year, and has the opportunity to determine optimal depot locations and vehicle routings by evaluating the best and the worst cases of demand quantity for ten years ahead.

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Engin Pekel, Yildiz Technical University

Engin PEKEL holds an MSc in Industrial Engineering and he is currently studying his PhD in Industrial Engineering. He has been working as a Research Assistant in the Department of Industrial Engineering.

Selin Soner Kara, Yildiz Technical University

Selin Soner Kara holds an MSc in Industrial Engineering and a PhD in Industrial Engineering. She is an Associate Professor in the department of Industrial Engineering at Yildiz Technical University.

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Published
2018-11-09
How to Cite
1.
Pekel E, Soner Kara S. Solving Capacitated Location Routing Problem by Variable Neighborhood Descent and GA-Artificial Neural Network Hybrid Method. Promet [Internet]. 2018Nov.9 [cited 2024Dec.22];30(5):563-78. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/2640
Issue
Vol 30 No 5 (2018)
Section
Articles

Copyright (c) 2018 Engin PEKEL, Selin SONER KARA

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