AN ARTIFICIAL NEURAL NETWORK APPROACH FOR THE LOGISTICS CENTER LOCATION SELECTION

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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