The Impact of Seasonal Demand Fluctuations On Service Network Design of Container Feeder Lines


Olcay Polat
Assist. Prof., Pamukkale University, Denizli, Turkey, opolat@pau.edu.tr

Hans-Otto Günther
Prof., Pusan National University, Busan, Korea, hans-otto.guenther@hotmail.de

Abstract

Customer demand in global supply networks is highly uncertain due to unexpected global and local economic conditions and, in addition, affected by seasonal demand fluctuations for final products. Therefore, in maritime transportation the design of short-sea shipping services for containerized goods has to prove its economic efficiency under varying conditions of transportation demand. Since liner shipping involves significant capital investments and huge daily operating costs, the appropriate design of the service network is crucial for the profitability of the container feeder lines. Usually, quantitative models for shipping network design are based on deterministic forecasts, which are prone to errors caused by uncertainty factors and structural changes in the development of demand. This paper puts special emphasis on the impact of seasonal demand fluctuations on the structure of the related H&S networks, the capacity of the fleet operating within the network, the deployment of ship types as well as on the associated routes of the ships. A simulation and artificial neural network based forecasting framework is developed to support the design of service networks of short-sea shipping lines. The proposed methodology has been tested for a feeder liner shipping service in the East Mediterranean and Black Sea region. Numerical results show that seasonal demand fluctuations have vital impact on the network design of container feeder lines.

Keywords: Feeder service network design, Container shipping, Forecasting, Simulation, Liner shipping, Artificial neural network, Seasonality

Mevsimsel Talep Dalgalanmalarının Besleyici Konteynır Hatlarının Servis Ağı Tasarımındaki Etkisi


Öz

Küresel tedarik ağlarındaki müşteri talebi beklenmedik küresel ve yerel ekonomik krizlerden dolayı oldukça belirsiz olup son ürünlerdeki mevsimsel talep dalgalanmalarından etkilenmektedir. Bu nedenle konteynır yükleri için denizyolu taşımacılığı servis tasarımları, değişen nakliye talepleri altında ekonomik etkinliklerini ortaya koymak zorundadırlar. Düzenli hat deniz yolu taşımacılığı önemli bir sermaye yatırımı içerdiğinden  uygun servis ağı tasarımı besleyici konteynır hatlarının karlılığı için çok önemlidir. Genellikle denizyolu taşımacılığı ağ tasarımı için kullanılan sayısal modeller, belirsizlik faktörleri ve talebin gelişimindeki yapısal değişiklikler nedeni ile hatalara neden olabilen deterministik tahminlemelere dayanmaktadır. Bu çalışma mevsimsel talep dalgalarının ilgili servis ağlarının yapısındaki etkisi, ağ içerisinde operasyon gösteren filonun kapasitesi, gemi tiplerinin açılımıyla birlikte gemilerin ilişkilendikleri rotaların belirlenmesine de özel vurgu yapmaktadır. Çalışmada, denizyolu taşımacılığı servis ağlarının tasarlanmasına destek sağlamak için bir benzetim ve yapay sinir ağı temelli tahminleme yapısı besleyici tasarlanmıştır. Önerilen yöntem doğu Akdeniz ve Karadeniz havzasındaki bir besleyici denizyolu taşımacılığı servisi için test edilmiştir. Sayısal sonuçlar mevsimsel talep dalgalanmalarının besleyici hatların servis tasarımları üzerinde hayati öneme sahip olduğunu göstermektedir

Anahtar Kelimeler: Besleyici servis ağı tasarımı, Konteynır taşıma, Tahminleme, Benzetim, Düzenli hat denizyolu taşımacılığı, Yapay sinir ağları, Mevsimsellik


Cite this article

Polat, O., Günther, H. (2016). The Impact of Seasonal Demand Fluctuations On Service Network Design of Container Feeder Lines. Journal of Transportation and Logistics, 1(1), 39-58. http://dx.doi.org/10.22532/jtl.237886

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Volume 1, Issue 1, 2016

Journal of Transportation and Logistics

Volume 1, Issue 1, 2016

Pages 39-58

Received: Feb. 2, 2016

Accepted: April 27, 2016

Published: April 30, 2016

Full Text [1.2 MB]

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2016 School of Transportation and Logistics at Istanbul University.