AN ARTIFICIAL NEURAL NETWORK APPROACH FOR THE LOGISTICS CENTER LOCATION SELECTION

Year 2017, , 107 - 115, 30.06.2017

Burcu Kaya Nursel Öztürk

https://doi.org/10.17261/Pressacademia.2017.455

Abstract

Purpose- The importance of the city freight transport is crucial when
the sustainable development of the city is considered. City logistics come up
against the environmental problems such as traffic congestion, air and noise
pollution. The importance of the analyzing and controlling the city logistics
activities is evident, considering the effects on the big cities that have a
considerable population, a developed industry, and considerable logistics
activities. The location selection decision of the logistics center is crucial
in terms of the efficient design of the network. The aim of this study is to
develop a system that intended to help decision makers decide the feasibility
of the potential location for the logistics centers by entering the input
values for the parameters of the location.  

Methodology- In this study, the factors such as accessibility,
costs, land feasibility, socio-economic and environmental factors is
considering as the critical factors in selecting the most suitable logistics
center location. An artificial neural network approach is proposed for the location
selection problem of the logistics centers.

Findings- The findings indicate that the parameter associated with the
socio-economic and environmental impact is crucial on logistics center location
decision. The output values of the neural network is compared with the real
values of the logistics center located in Turkey. The test results indicate
that the artificial neural network gives feasible outputs by entering the input
values that are not include in the training datasets.

Conclusion- The factors affecting logistics center location
decision are socio-economic and environmental, accessibility, land feasibility
and costs, respectively. As a result of this study, the
developed neural network is not only help the decision makers to choose the
feasible logistics center location through the alternatives but also decide the
feasibility of any location by entering the value of the input parameters. 

Keywords

Logistics center, artificial neural network, location selection

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