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Açık Kaynak CBS ile Şehiriçi Kargo İstasyon Noktalarının Optimizasyonu ve Dağıtım Planlaması

Yıl 2021, Cilt: 36 Sayı: 4, 989 - 996, 29.12.2021
https://doi.org/10.21605/cukurovaumfd.1040769

Öz

Kargo ve taşımacılık sektörü her geçen gün daha da büyümektedir. Sektördeki büyüme ve müşteri isteklerindeki hızlı teslimat talebi karşısında kaynakların daha verimli yönetilmesi gerekmektedir. Kaynakların daha verimli yönetilebilmesi için kargo şubelerinin yer seçimi ve kargo araçlarının güzergah planlama süreçleri önem arz etmektedir. Yer seçimi ve güzergah planlama sürecinde Coğrafi Bilgi Sistemleri (CBS) önemli avantajlar sağlamaktadır. Özellikle açık kaynak kodlu CBS verileri ve CBS yazılımları düşük maliyetli ve etkin çözümler sunmaktadır. Bu çalışmada Gaziantep ilinin Şehitkamil ilçesinde bir kargo firmasının şube yerleri irdelenmiş ve araçlara ait güzergahlar zaman kaybını ve yakıt tüketimini en aza indirecek şekilde analiz edilmiştir. Bu kapsamda yol ağı üzerinden isochrone haritalar üretilmiş. Bu isochrone bölgeleri içerisinde var olan nüfus sayıları hesaplanmış ve nüfus verilerine göre araç sorumluluk bölgeleri belirlenmiştir. Son olarak ta kargo araçlarının bir gün içerisinde teslimat yapması gereken yüzün üzerinde kargonun günlük rota planlaması yapılmıştır.

Kaynakça

  • 1. İndap, Ş., 2019. The Status of Cargo Companies in E-Commerce Logistics and Innovative Solution Proposals to Improve Their Competitiveness. Girişimcilik ve İnovasyon Yönetim Dergisi, 8(2), 39-67.
  • 2. Memon, I. A., 2005. Application of Geographic Information System in Transportation for Road Network Analysis (M.Sc). Universiti Teknologi Malaysia, Faculty of Civil Engineering.
  • 3. Abousaeidi, M., Fauzi R., Muhamad, R., 2016. Geographic Information System (GIS) Modeling Approach to Determine the Fastest Delivery Routes. Saudi J Biol Sci 23:555–564. https://doi.org/https://doi.org/10.1016/j.sjbs.2015.06.004.
  • 4. Azaz L., 2011. The Use of Geographic Information Systems (GIS) in Business. International Conference on Humanities. Geography and Economics (ICHGE'2011) Pattaya Dec., 2011
  • 5. El Raoui H, Oudani M, Alaoui AEH., 2018. ABM-GIS Simulation for Urban Freight Distribution of Perishable Food. MATEC Web Conf.
  • 6. Sassi, E., Benabdelhafid, A., 2020. The Complexity of the Territorial Logistics Ecosystem. 13ème Conference Internationale de Modelisation, Optimisation et Simulation (MOSIM2020), 12-14 Nov 2020, AGADIR, Maroc, Nov 2020, AGADIR (virtual), Morocco.
  • 7. Akter, T., Hernandez, S., Diaz Corro, K., Ngo, C., 2018. Leveraging Open-source GIS Tools to Determine Freight Activity Patterns from Anonymous GPS Data.
  • 8. Widaningrum, D.L., 2015. A GIS-based Approach for Catchment Area Analysis of Convenience Store. Procedia Comput Sci 72, 511–518.
  • 9. Wong, E.Y.C., Tai, A.H., So, S., 2020. 'Container Drayage Modelling with Graph Theory-based Road Connectivity Assessment for Sustainable Freight Transportation in New Development Area. Computers and Industrial Engineering, 149(106810), 1-11. doi.org/10.1016/j.cie.2020.106810.
  • 10. Yu, Y.W., Jung, H., Bae, H., 2015. Integrated GIS-based Logistics Process Monitoring Framework with Convenient Work Processing Environment for Smart Logistics. ETRI J 37, 306–316. doi.org/10.4218/etrij.15.2314.00 56.
  • 11. Yücel, M.M., Ulutaş, A., 2009. Çok Kriterli Karar Yöntemlerinden Electre Yöntemiyle Malatya’da Bir Kargo Firması için Yer Seçimi. Sosyal Ekonomik Araştırmalar Dergisi, no.17, 327-344.
  • 12. Chandra, A., Pani, A., Sahu, P.K., 2020. Designing Zoning Systems for Freight Transportation Planning: A GIS-based Approach for Automated Zone Design Using Public Data Sources. Transp Res Procedia 48:605–619. https://doi.org/10.1016/j.trpro. 2020.08.063.
  • 13. Cecílio, I., Chiquieri, J., Freitas, R., Goncalves, W., 2019. Holistic Analysis of the Vehicle Routing Problem: an Approach for GIS-T. Int J Adv Eng Res Sci, 6, 116–131. https://doi.org/10.22161/ijaers.69.13.
  • 14. Kozhakhmeto, S., Zakiev, E., 2020. Possible Ways to Implement GIS Technologıes in the Logistics Management System in Order to Improve Management Efficiency. International Journal of Advanced Research in Engineering and Technology (IJARET) Volume 11, Issue 12, December 2020, 1546-1554.
  • 15. Allen, J., 2018. Using Network Segments in the Visualization of Urban Isochrones. Cartogr Int J. Geogr. Inf Geovisualization, 53, 262–270. https://doi.org/10.3138/cart.53.4. 2018-0013.

Optimization of Urban Cargo Distribution Network and Station Points with Open Source GIS

Yıl 2021, Cilt: 36 Sayı: 4, 989 - 996, 29.12.2021
https://doi.org/10.21605/cukurovaumfd.1040769

Öz

The cargo and transportation sector is growing day by day. Resources need to be managed more efficiently in the face of growth in the sector and fast delivery demand in customer requests. Location selection of cargo branches and route planning processes of cargo vehicles are important in order to manage resources more efficiently. Geographic Information Systems (GIS) provide significant advantages in site selection and route planning processes. Especially open source GIS data and GIS software offer low cost and effective solutions. In this study, the branch locations of a cargo company in ġehitkamil district of Gaziantep province were examined and the routes of the vehicles were analyzed in a way to minimize time loss and fuel consumption. In this context, isochrone maps were produced over the road network. The population numbers within these isochrone zones were calculated and vehicle liability zones were determined according to the population data. Finally, the daily route planning of more than a hundred cargoes, which are required to be delivered by cargo vehicles in one day, has been made.

Kaynakça

  • 1. İndap, Ş., 2019. The Status of Cargo Companies in E-Commerce Logistics and Innovative Solution Proposals to Improve Their Competitiveness. Girişimcilik ve İnovasyon Yönetim Dergisi, 8(2), 39-67.
  • 2. Memon, I. A., 2005. Application of Geographic Information System in Transportation for Road Network Analysis (M.Sc). Universiti Teknologi Malaysia, Faculty of Civil Engineering.
  • 3. Abousaeidi, M., Fauzi R., Muhamad, R., 2016. Geographic Information System (GIS) Modeling Approach to Determine the Fastest Delivery Routes. Saudi J Biol Sci 23:555–564. https://doi.org/https://doi.org/10.1016/j.sjbs.2015.06.004.
  • 4. Azaz L., 2011. The Use of Geographic Information Systems (GIS) in Business. International Conference on Humanities. Geography and Economics (ICHGE'2011) Pattaya Dec., 2011
  • 5. El Raoui H, Oudani M, Alaoui AEH., 2018. ABM-GIS Simulation for Urban Freight Distribution of Perishable Food. MATEC Web Conf.
  • 6. Sassi, E., Benabdelhafid, A., 2020. The Complexity of the Territorial Logistics Ecosystem. 13ème Conference Internationale de Modelisation, Optimisation et Simulation (MOSIM2020), 12-14 Nov 2020, AGADIR, Maroc, Nov 2020, AGADIR (virtual), Morocco.
  • 7. Akter, T., Hernandez, S., Diaz Corro, K., Ngo, C., 2018. Leveraging Open-source GIS Tools to Determine Freight Activity Patterns from Anonymous GPS Data.
  • 8. Widaningrum, D.L., 2015. A GIS-based Approach for Catchment Area Analysis of Convenience Store. Procedia Comput Sci 72, 511–518.
  • 9. Wong, E.Y.C., Tai, A.H., So, S., 2020. 'Container Drayage Modelling with Graph Theory-based Road Connectivity Assessment for Sustainable Freight Transportation in New Development Area. Computers and Industrial Engineering, 149(106810), 1-11. doi.org/10.1016/j.cie.2020.106810.
  • 10. Yu, Y.W., Jung, H., Bae, H., 2015. Integrated GIS-based Logistics Process Monitoring Framework with Convenient Work Processing Environment for Smart Logistics. ETRI J 37, 306–316. doi.org/10.4218/etrij.15.2314.00 56.
  • 11. Yücel, M.M., Ulutaş, A., 2009. Çok Kriterli Karar Yöntemlerinden Electre Yöntemiyle Malatya’da Bir Kargo Firması için Yer Seçimi. Sosyal Ekonomik Araştırmalar Dergisi, no.17, 327-344.
  • 12. Chandra, A., Pani, A., Sahu, P.K., 2020. Designing Zoning Systems for Freight Transportation Planning: A GIS-based Approach for Automated Zone Design Using Public Data Sources. Transp Res Procedia 48:605–619. https://doi.org/10.1016/j.trpro. 2020.08.063.
  • 13. Cecílio, I., Chiquieri, J., Freitas, R., Goncalves, W., 2019. Holistic Analysis of the Vehicle Routing Problem: an Approach for GIS-T. Int J Adv Eng Res Sci, 6, 116–131. https://doi.org/10.22161/ijaers.69.13.
  • 14. Kozhakhmeto, S., Zakiev, E., 2020. Possible Ways to Implement GIS Technologıes in the Logistics Management System in Order to Improve Management Efficiency. International Journal of Advanced Research in Engineering and Technology (IJARET) Volume 11, Issue 12, December 2020, 1546-1554.
  • 15. Allen, J., 2018. Using Network Segments in the Visualization of Urban Isochrones. Cartogr Int J. Geogr. Inf Geovisualization, 53, 262–270. https://doi.org/10.3138/cart.53.4. 2018-0013.
Toplam 15 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Şevket Bediroğlu Bu kişi benim 0000-0002-7216-6910

Yayımlanma Tarihi 29 Aralık 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 36 Sayı: 4

Kaynak Göster

APA Bediroğlu, Ş. (2021). Optimization of Urban Cargo Distribution Network and Station Points with Open Source GIS. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 36(4), 989-996. https://doi.org/10.21605/cukurovaumfd.1040769