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Bulanık PERT Yöntemiyle Lojistik İç Taşıma Süreç Analizi

Yıl 2021, Cilt: 5 Sayı: 1, 211 - 230, 26.01.2021
https://doi.org/10.29023/alanyaakademik.697529

Öz

Lojistik süreçlerin en önemli halkalarından biri taşımacılık süreçleridir. Taşımacılık süreçleri, ana taşıma noktası olan terminallere ulaşmayı kapsayan ön taşıma, ana taşıma ve varış terminalinden alıcıya olan ulaşımı kapsayan son taşıma süreçlerinden oluşmaktadır. Ön taşıma ve son taşıma süreçleri genel olarak iç taşıma olarak adlandırılmakla beraber; ön taşımayı ihracat iç taşıma, son taşımayı ise ithalat iç taşıma olarak ifade edebiliriz. Ana taşıma süreci kadar, etkin bir taşıma süreci için iç taşıma sürecinin de eksiksiz bir şekilde yönetilmesi önemlidir. Bu bakımdan çalışmada, deniz ithalat ve ihracat iç taşıma süreçlerinin analizi bulanık PERT yöntemiyle yapılmış olup, her bir sürecin tamamlanma süreleri ve kritik yol ve süreleri tespit edilmiştir. Bununla birlikte; her bir sürecin faaliyetleri ve süreleri bir lojistik firmanın ilgili departmanı tarafından tespit edilmiştir.

Kaynakça

  • ABDELBAR M.K. &BOUAMI D. &ELFEZAZI S. (2019). "New approach towards formulation of the overall equipment effectiveness", Journal of Quality in Maintenance Engineering, Vol. 25 Issue: 1, pp.90-127,
  • AGHDAREH S.A.&, EGHBALI H.& AMADANDI M. (2019). Designing a risk management model for continuously reinforced concrete pavement (CRCP) using network analysis (October 27, 2019).
  • BELLMAN. R.E. & ZADEH. L.A., (1970). Decision-making in a fuzzy environment, Management Science. vol.17. no.4. pp.141–164.
  • BERGQVIST R. & BEHRENDS S. (2011). Assessing the effects of longer vehicles: the case of pre- and post-haulage in intermodal transport chains, Transport Reviews, 31:5, 591-602.
  • BERQVIST R.& MONIOS J. (2016). The last mile, inbound logistics and intermodal high capacity transport – the case of Jula in Sweden, World Review of Intermodal Transportation Research • July 2016, 6 (1): 74-92.
  • CALP M.H.& AKCAYOL M. A. (2018). Optimization of project scheduling activities in dynamic CPM and PERT networks using genetic algorithms, Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi Cilt 22, Sayı 2, 615-627.
  • CARIS, A. & JANSSENS G.K. (2010). A deterministic annealing algorithm for the pre- and end-haulage of intermodal container terminals, International Journal of Computer Aided Engineering and Technology2010 Vol.2 No.4.
  • CHANAS, S., (1982). Fuzzy sets in few classical operational research problems. In Approximate Reasoning in Decision Analysis (Eds M. M. Gupta and E. Sanchez), pp. 351-363. North-Holland, New York. CHANAS S. & KAMBUROWSKI J (1981). The use of fuzzy variables in PERT, Fuzzy Sets and Systems 5 (1981) 11-19.
  • CHEN C.T. & HUANG S.F. (2007). Applying fuzzy method for measuring criticality in project network, Information Sciences 177 (2007) 2448–2458.
  • CHEN S.P. & HSUEH Y.J. (2008). A simple approach to fuzzy critical path analysis in project Networks, Applied Mathematical Modelling 32 (2008) 1289–1297.
  • COLLIER Z.A., HENDRICKSON D., POLMATEER T.L., Lambert J.H. (2018). Scenario analysis and PERT/CPM applied to strategic investment at an automated container port, ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng., 2018, 4(3): 04018026.
  • DTO (2019) Denizcilik Sektör Raporu İMEAK Deniz Ticaret Odası, İstanbul,2019.
  • ESCUDERO, A., MUÑUZURI, J., GUADIX, J., & ARANGO, C. (2013). “Dynamic approach to solve the daily drayage problem with transit time uncertainty”. Computers in industry, 64(2), 165-175.
  • FUNKE, J., & KOPFER, H. (2016). “A model for a multi-size inland container transportation problem”. Transportation Research Part E: Logistics and Transportation Review, 89, 70-85.
  • GENCER C. & TÜRKBEY O. (2001). Proje tamamlanma zamanının bulunmasında istatistiksel analiz yardımıyla Bulanık- PERT, Klasik- PERT ve gerçek-dağılımyöntemlerininkarşılaştırılması, DEÜ MühendislikFakültesi Fen veMühendislikDergisiCilt: 3 Sayı: 2 S. 29-39.
  • HABIBI F., BIRGANI O.T., KOPPELAAR H. & RADENOVIĆ S. (2018). Using fuzzy logic to improve the project time and cost estimation based on Project Evaluation and Review Technique (PERT), Journal of Project Management 3 (2018) 183–196.
  • HSIEH, T. Y., LU, S. T., & TZENG, G. H., (2004). Fuzzy MCDM approach for planning and design tender’s selection in public office buildings, International Journal of Project Management, 22(7), 573–584.
  • KAUFMANN, A. & GUPTA, M.M., (1988). Fuzzy Mathematical Models in Engineering and Management Science, North Holland, Amsterdam.
  • KAUFMANN, A. & GUPTA, M.M., (1991). Introduction to Fuzzy Arithmetic, Van Nostrand, New York,
  • KOCABIYIK, E. (2009). Gemi inşa sektöründe faaliyet gösteren bir işletmede PERT ve bulanık PERT uygulaması, Yıldız Teknik Üniversitesi Fen Bilimleri Enstitüsü Endüstri Mühendisliği Anabilim Dalı, Sistem Mühendisliği Programı, Yüksek Lisans Tezi, İstanbul.
  • KURTULUŞ, E. & ÇETIN İ.B. (2020), Analysis of modal shift potential towards intermodal transportation in short- distance inland container transport, Transport Policy,Volume 89, p. 24-37.
  • LAUDARES, A.B., RICCO M.F.F & SANTOS, R.A.S. (2019).When does it end? Monte carlo simulation applied to risk management in defense logistics’ procurement processes, Brazilian Journal of Operations & Production Management 16 (2019), pp 149-156, ABEPRO, DOI: 10.14488/BJOPM. 2019.v16.n1.a14.
  • LI R. J. & LEE, E. S., (1987). Ranking fuzzy numbers a comparison. Proc. of NAFIPS, May 5-7, West Lafayette, Indiana.
  • LI, L., NEGENBORN, R.R.& SHUTTER B.D. (2014) Receding horizon approach for container flow assignment in intermodal freight transport, Transportation Research Record Journal of the Transportation Research Board 2410(2410):132-140.
  • MACHARIS, C., & BONTEKONING, Y. M. (2004). “Opportunities for OR in intermodal freight transport research: A review”. European Journal of operational research, 153(2), 400-416.
  • MAZLUM, M. (2014). CPM, PERT vebulanıkmantıkteknikleriyleprojeyönetimivebirişletmedeuygulanması, Yıldız Teknik Üniversitesi Fen Bilimleri Enstitüsü Endüstri Mühendisliği Anabilim Dalı, Endüstri Mühendisliği Programı, Yüksek Lisans Tezi, İstanbul.
  • MCCAHON C.S. & LEE E.S. (1988). Project network analysis with fuzzy activity times, Computers and Mathematics Applications, 15 (10):829-838.
  • ODIJK, M. (2009). Analyzing the pre-and end-haulage of maritime containers in collaborative networks. Master of Science in Operations Management and Logistics, Technische Universiteit Eindhoven, Eindhoven.
  • OPRICOVIC, S. & TZENG, G.H., (2003). Defuzzification within a fuzzy multicriteria decision model, International Journal of Uncertainty, Fuzziness and Knowledge-based Systems. 11, 635–652.
  • SACKEY, S & KIM,B.S. (2019). Schedule risk analysis using a proposed modified variance and mean of the original program evaluation and review technique model, KSCE Journal of Civil Engineering (2019) 23(4):1484-1492.
  • TAKAKURA, Y., YAJIMAA, T., KAWAJIRIA, Y., HASHIZUMECA, S. (2019).Application of critical path method to stochastic processes with historical operation data, Chemical Engineering Research and Design 1 4 9 ( 2 0 1 9 ) 195–208.
  • TATTERSON, J.W.& WOOD, D.F. (1974). PERT, CPM and the export process, OMEGA, The Int. Jl of Mgmt Sci., Vol. 2, No. 3,421-426.
  • VALERO, M.F., MENÉNDEZ, L.G., CARRAMOLINO, L.S.& PRUÑONOSA, S.F. (2011). The importance of the inland leg of containerised maritime shipments: An analysis of modal choice determinants in Spain, Transportation Research Part E 47 (2011) 446–460.
  • VANÍČKOVÁ,R. (2019). Changes in lifestyle of population and solutions in logistics of bakery products: practice in the Czech Republic,Advances in Economics, Business and Management Research, volume 78, 83-92, 11th International Scientific Conference "Economics, Management and Technology in Enterprises 2019" (EMT 2019).
  • WIEGMANS,B. &KONINGS,R. (2013). The performance of intermodal inland waterway transport: Modeling conditions influencing its competitiveness, WCTR 2013 Rio 13th World Conference on Transport Research 13-18 July 2013, Rio de Janeiro, Brazil.
  • ZADEH L.A., (1965).Fuzzy sets, Inform. Control 8 (3) 338–353.

Logistics Inland Haulage Process Analysis with Fuzzy PERT Method

Yıl 2021, Cilt: 5 Sayı: 1, 211 - 230, 26.01.2021
https://doi.org/10.29023/alanyaakademik.697529

Öz

One of the most important rings of logistics processes is transportation processes. Transportation processes consist of pre-carriage, which includes the transportation to the terminals, the main transportation, and the on-carriage, which includes the transportation from the main transportation and arrival terminal to the buyer. While the pre-carriage and on-carriage processes are generally called inland haulage, we can refer to the front transport as export pre-carriage, the last transport as import on-carriage. For an efficient transportation process, it is important to manage the inland haulage process as well as the main transportation process. In this regard, the analysis of the sea import and export inland haulage processes is carried out using the fuzzy PERT method, and the completion times and critical paths and times of each process were determined. However, the activities and durations of each process have been determined by the relevant department of a logistics company.

Kaynakça

  • ABDELBAR M.K. &BOUAMI D. &ELFEZAZI S. (2019). "New approach towards formulation of the overall equipment effectiveness", Journal of Quality in Maintenance Engineering, Vol. 25 Issue: 1, pp.90-127,
  • AGHDAREH S.A.&, EGHBALI H.& AMADANDI M. (2019). Designing a risk management model for continuously reinforced concrete pavement (CRCP) using network analysis (October 27, 2019).
  • BELLMAN. R.E. & ZADEH. L.A., (1970). Decision-making in a fuzzy environment, Management Science. vol.17. no.4. pp.141–164.
  • BERGQVIST R. & BEHRENDS S. (2011). Assessing the effects of longer vehicles: the case of pre- and post-haulage in intermodal transport chains, Transport Reviews, 31:5, 591-602.
  • BERQVIST R.& MONIOS J. (2016). The last mile, inbound logistics and intermodal high capacity transport – the case of Jula in Sweden, World Review of Intermodal Transportation Research • July 2016, 6 (1): 74-92.
  • CALP M.H.& AKCAYOL M. A. (2018). Optimization of project scheduling activities in dynamic CPM and PERT networks using genetic algorithms, Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi Cilt 22, Sayı 2, 615-627.
  • CARIS, A. & JANSSENS G.K. (2010). A deterministic annealing algorithm for the pre- and end-haulage of intermodal container terminals, International Journal of Computer Aided Engineering and Technology2010 Vol.2 No.4.
  • CHANAS, S., (1982). Fuzzy sets in few classical operational research problems. In Approximate Reasoning in Decision Analysis (Eds M. M. Gupta and E. Sanchez), pp. 351-363. North-Holland, New York. CHANAS S. & KAMBUROWSKI J (1981). The use of fuzzy variables in PERT, Fuzzy Sets and Systems 5 (1981) 11-19.
  • CHEN C.T. & HUANG S.F. (2007). Applying fuzzy method for measuring criticality in project network, Information Sciences 177 (2007) 2448–2458.
  • CHEN S.P. & HSUEH Y.J. (2008). A simple approach to fuzzy critical path analysis in project Networks, Applied Mathematical Modelling 32 (2008) 1289–1297.
  • COLLIER Z.A., HENDRICKSON D., POLMATEER T.L., Lambert J.H. (2018). Scenario analysis and PERT/CPM applied to strategic investment at an automated container port, ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng., 2018, 4(3): 04018026.
  • DTO (2019) Denizcilik Sektör Raporu İMEAK Deniz Ticaret Odası, İstanbul,2019.
  • ESCUDERO, A., MUÑUZURI, J., GUADIX, J., & ARANGO, C. (2013). “Dynamic approach to solve the daily drayage problem with transit time uncertainty”. Computers in industry, 64(2), 165-175.
  • FUNKE, J., & KOPFER, H. (2016). “A model for a multi-size inland container transportation problem”. Transportation Research Part E: Logistics and Transportation Review, 89, 70-85.
  • GENCER C. & TÜRKBEY O. (2001). Proje tamamlanma zamanının bulunmasında istatistiksel analiz yardımıyla Bulanık- PERT, Klasik- PERT ve gerçek-dağılımyöntemlerininkarşılaştırılması, DEÜ MühendislikFakültesi Fen veMühendislikDergisiCilt: 3 Sayı: 2 S. 29-39.
  • HABIBI F., BIRGANI O.T., KOPPELAAR H. & RADENOVIĆ S. (2018). Using fuzzy logic to improve the project time and cost estimation based on Project Evaluation and Review Technique (PERT), Journal of Project Management 3 (2018) 183–196.
  • HSIEH, T. Y., LU, S. T., & TZENG, G. H., (2004). Fuzzy MCDM approach for planning and design tender’s selection in public office buildings, International Journal of Project Management, 22(7), 573–584.
  • KAUFMANN, A. & GUPTA, M.M., (1988). Fuzzy Mathematical Models in Engineering and Management Science, North Holland, Amsterdam.
  • KAUFMANN, A. & GUPTA, M.M., (1991). Introduction to Fuzzy Arithmetic, Van Nostrand, New York,
  • KOCABIYIK, E. (2009). Gemi inşa sektöründe faaliyet gösteren bir işletmede PERT ve bulanık PERT uygulaması, Yıldız Teknik Üniversitesi Fen Bilimleri Enstitüsü Endüstri Mühendisliği Anabilim Dalı, Sistem Mühendisliği Programı, Yüksek Lisans Tezi, İstanbul.
  • KURTULUŞ, E. & ÇETIN İ.B. (2020), Analysis of modal shift potential towards intermodal transportation in short- distance inland container transport, Transport Policy,Volume 89, p. 24-37.
  • LAUDARES, A.B., RICCO M.F.F & SANTOS, R.A.S. (2019).When does it end? Monte carlo simulation applied to risk management in defense logistics’ procurement processes, Brazilian Journal of Operations & Production Management 16 (2019), pp 149-156, ABEPRO, DOI: 10.14488/BJOPM. 2019.v16.n1.a14.
  • LI R. J. & LEE, E. S., (1987). Ranking fuzzy numbers a comparison. Proc. of NAFIPS, May 5-7, West Lafayette, Indiana.
  • LI, L., NEGENBORN, R.R.& SHUTTER B.D. (2014) Receding horizon approach for container flow assignment in intermodal freight transport, Transportation Research Record Journal of the Transportation Research Board 2410(2410):132-140.
  • MACHARIS, C., & BONTEKONING, Y. M. (2004). “Opportunities for OR in intermodal freight transport research: A review”. European Journal of operational research, 153(2), 400-416.
  • MAZLUM, M. (2014). CPM, PERT vebulanıkmantıkteknikleriyleprojeyönetimivebirişletmedeuygulanması, Yıldız Teknik Üniversitesi Fen Bilimleri Enstitüsü Endüstri Mühendisliği Anabilim Dalı, Endüstri Mühendisliği Programı, Yüksek Lisans Tezi, İstanbul.
  • MCCAHON C.S. & LEE E.S. (1988). Project network analysis with fuzzy activity times, Computers and Mathematics Applications, 15 (10):829-838.
  • ODIJK, M. (2009). Analyzing the pre-and end-haulage of maritime containers in collaborative networks. Master of Science in Operations Management and Logistics, Technische Universiteit Eindhoven, Eindhoven.
  • OPRICOVIC, S. & TZENG, G.H., (2003). Defuzzification within a fuzzy multicriteria decision model, International Journal of Uncertainty, Fuzziness and Knowledge-based Systems. 11, 635–652.
  • SACKEY, S & KIM,B.S. (2019). Schedule risk analysis using a proposed modified variance and mean of the original program evaluation and review technique model, KSCE Journal of Civil Engineering (2019) 23(4):1484-1492.
  • TAKAKURA, Y., YAJIMAA, T., KAWAJIRIA, Y., HASHIZUMECA, S. (2019).Application of critical path method to stochastic processes with historical operation data, Chemical Engineering Research and Design 1 4 9 ( 2 0 1 9 ) 195–208.
  • TATTERSON, J.W.& WOOD, D.F. (1974). PERT, CPM and the export process, OMEGA, The Int. Jl of Mgmt Sci., Vol. 2, No. 3,421-426.
  • VALERO, M.F., MENÉNDEZ, L.G., CARRAMOLINO, L.S.& PRUÑONOSA, S.F. (2011). The importance of the inland leg of containerised maritime shipments: An analysis of modal choice determinants in Spain, Transportation Research Part E 47 (2011) 446–460.
  • VANÍČKOVÁ,R. (2019). Changes in lifestyle of population and solutions in logistics of bakery products: practice in the Czech Republic,Advances in Economics, Business and Management Research, volume 78, 83-92, 11th International Scientific Conference "Economics, Management and Technology in Enterprises 2019" (EMT 2019).
  • WIEGMANS,B. &KONINGS,R. (2013). The performance of intermodal inland waterway transport: Modeling conditions influencing its competitiveness, WCTR 2013 Rio 13th World Conference on Transport Research 13-18 July 2013, Rio de Janeiro, Brazil.
  • ZADEH L.A., (1965).Fuzzy sets, Inform. Control 8 (3) 338–353.
Toplam 36 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ekonomi
Bölüm Makaleler
Yazarlar

Sibel Bayar 0000-0002-9169-935X

Ercan Akan 0000-0003-0383-8290

Yayımlanma Tarihi 26 Ocak 2021
Kabul Tarihi 30 Eylül 2020
Yayımlandığı Sayı Yıl 2021 Cilt: 5 Sayı: 1

Kaynak Göster

APA Bayar, S., & Akan, E. (2021). Bulanık PERT Yöntemiyle Lojistik İç Taşıma Süreç Analizi. Alanya Akademik Bakış, 5(1), 211-230. https://doi.org/10.29023/alanyaakademik.697529