Transport Routes Optimization Model Through Application of Fuzzy Logic

  • Ivan Bortas Arhitektika projekt d.o.o. Samobor
  • Nikolina Brnjac Fakultet prometnih znanosti, SveučiliÅ¡ta u Zagrebu
  • Čedomir Dundović Pomorski fakultet, SveučiliÅ¡ta u Rijeci
Keywords: intermodal transport, optimization of transport routes, reduction of environmental pollution, fuzzy logic,

Abstract

The transport policy of the European Union is based on the mission of restructuring road traffic into other and energy-favourable transport modes which have not been sufficiently represented yet. Therefore, the development of the inland waterway and rail transport, and connectivity in the intermodal transport network are development planning priorities of the European transport strategy. The aim of this research study was to apply the scientific methodology and thus analyse the factors that affect the distribution of the goods flows and by using the fuzzy logic to make an optimization model, according to the criteria of minimizing the costs and negative impact on the environment, for the selection of the optimal transport route. Testing of the model by simulation, was performed on the basis of evaluating the criteria of the influential parameters with unprecise and indefinite input parameters. The testing results show that by the distribution of the goods flow from road transport network to inland waterways or rail transport, can be predicted in advance and determine the transport route with optimal characteristics. The results of the performed research study will be used to improve the process of planning the transport service, with the aim of reducing the transport costs and environmental pollution.

Author Biographies

Ivan Bortas, Arhitektika projekt d.o.o. Samobor
dipl.ing.
Nikolina Brnjac, Fakultet prometnih znanosti, Sveučilišta u Zagrebu
dr.sc.
Čedomir Dundović, Pomorski fakultet, SveučiliÅ¡ta u Rijeci
dr.sc.

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Published
2018-03-01
How to Cite
1.
Bortas I, Brnjac N, Dundović Č. Transport Routes Optimization Model Through Application of Fuzzy Logic. PROMET [Internet]. 2018Mar.1 [cited 2019Nov.19];30(1):121-9. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/2326
Section
Articles