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A RESEARCH ON MODELS PROPOSED FOR QUAY CRANE SCHEDULING PROBLEM IN CONTAINER TERMINALS

Yıl 2017, Cilt: 9 Sayı: 2, 136 - 161, 01.12.2017
https://doi.org/10.18613/deudfd.351634

Öz

Ports within the international logistics and supply chain system
constitute an important link of transport main activity. Port operations
directly and indirectly affect all logistics processes. It is necessary to
optimize these processes considering the increasing inter-port competition.
Especially the efficiency of quay cranes used in port operations has an important
effect on the port capacity and the waiting time of the vessels in ports. Thus,
many models have been proposed to obtain optimal efficiency from quay crane
operations. The study aims to examine and discuss the models proposed in the
literature to solve the quay crane scheduling problem in the container
terminals.

As a result
of the bibliometric analysis, it has been understood that the genetic algorithm
is the most frequently used solution algorithm in the 21 different solution
methods used in the proposed models. It has also been determined that
artificial intelligence is the most preferred approach. The research also
reveals that the rapidly developing technology has a direct impact on the
infrastructure of ports, that ports need fast handling cranes and that
innovative solution models should be developed in this direction.

Kaynakça

  • Al-Dhaheri, N. ve Diabat, A. (2015). The quay crane scheduling problem. Journal of Manufacturing Systems, 36, 87-94.
  • Al-Dhaheri, N. ve Diabat, A. (2016). A Lagrangian relaxation-based heuristic for the multi-ship quay crane scheduling problem with ship stability constraints. Annals and Operation Research, 24 (1).
  • Al-Dhaheri, N., Jebali, A. ve Diabat, A. (2016a). A simulation-based genetic algorithm approach f-for the quay crane scheduling under uncertainty. Simulation Modelling Practice and Theory, 66, 122-138.
  • Al-Dhaheri, N., Jebali, A. ve Diabat, A. (2016b). The quay crane scheduling problem with nonzero crane repositioning time and vessel stability constraints. Computers and Industrial Engineering, 94, 230-244.
  • Aras, N., Türkoğulları, Y., Taşkın, Z.C. ve Altınel, K. (2014). Simultaneous optimization of berth allocation, quay crane assignment and quay crane scheduling problems in container terminals. In: Operations Research Proceedings 2012, Springer International Publishing, 101-107.
  • Beens, M.A. ve Ursavaş, E. (2016). Scheduling cranes at an indented berth. European Journal of Operational Research, 253, 298-313.
  • Bierwirth, C. ve Meisel, F. (2010). A survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operational Research, 202, 615-627.
  • Bierwirth, C. ve Meisel, F. (2015). A follow-up survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operational Research, 244, 675-689.
  • Çağlar, V., Esmer, S. ve Bilgin, A. (2015). Mega konteyner gemilerinin tedarik zinciri ve limanlar üzerindeki etkileri. II. Ulusal Liman Kongresi Bildiriler Kitabı, İzmir.
  • Chen, J.H., Lee, D.H. ve Cao, J.X. (2012). A combinatorial benders’ cuts algorithm for the quayside operation problem at container terminals. Transportation Research Part E: Logistics and Transportation Review, 48, 266-275.
  • Chen, J.H., Lee, D.H. ve Goh, M. (2014). An effective mathematical formulation for the unidirectional cluster-based quay crane scheduling problem. European Journal of Operational Research, 232, 198-208.
  • Chung, S.H. ve Chan, T.S. (2013). A workload balancing genetic algorithm for the quay crane scheduling problem. International Journal of Production Research, 51, 4820-4834.
  • Chung, S.H. ve Choy, K.L. (2012). A modified genetic algorithm for quay crane scheduling operations. Expert Systems with Applications, 39, 4213-4221.
  • Daganzo, C.F. (1989). The crane scheduling problem. Transportation Research Part B: Methodological, 23, 159-175.
  • Davarzani, H., Fahimnia, B., Bell, M. ve Sarkis, J. (2016). Greening ports and maritime logistics: A review. Transportation Research Part D: Transport and Environment, 48, 473-487.
  • Diabat, A. ve Theodorou, E. (2014). An integrated quay crane assignment and scheduling problem. Computers and Industrial Engineering, 73, 115-123.
  • Fu, Y.M. ve Diabat, A. (2015). A Lagrangian relaxation approach for solving the integrated quay crane assignment and scheduling problem. Applied Mathematical Modelling, 39, 1194-1201.
  • Fu, Y.M., Diabat, A. ve Tsai, I.T. (2014). A multi-vessel quay crane assignment and scheduling problem: formulation and heuristic solution approach. Expert Systems with Applications, 41, 6959-6965.
  • Guan, Y., Yang, K.H. ve Zhou, Z. (2013). The crane scheduling problem: models and solution approaches. Annals and Operations Research, 203, 119-139.
  • Guo, P., Cheng, W ve Wang, Y. (2014). A modified generalized extremal optimization algorithm for the quay crane scheduling problem with interference constraints. Engineering Optimization, 46, 1411-1429.
  • Hakam, M.H., Solvang, W.D. ve Hammervoll, T. (2012). A genetic algorithm approach for quay crane scheduling with non-interference constraints at Narvik Container Terminal. International Journal of Logistics: Research and Applications, 15, 269-281.
  • He, J., Huang, Y., Yan, W. ve Wang, S. (2015). Integrated internal truck, yard crane and quay crane scheduling in a container terminal considering energy consumption. Expert System with Applications, 42, 2464-2487.
  • Iris, Ç., Pacino, D., Ropke, S. ve Larsen, A. (2015). Integrated berth allocation and quay crane assignment problem: set partitioning models and computational results. Transportation Research Part E: Logistics and Transportation Review, 81, 75-97.
  • Izquierdo, C.E., Velarde, J.L.G., Batista, B.M. ve Vega, J.M.M. (2013). Hybrid estimation of distribution algorithm for the quay crane scheduling problem. Applied Soft Computing, 13, 4063-4076.
  • Izquierdo, C.E., Ruiz, E.L., Batista, B.M. ve Vega, J.M.M. (2014). A study of rescheduling strategies for the quay crane scheduling problem under random disruptions. Inteligencia Artificial, 54, 35-47.
  • Kaveshgar, N. ve Huynh, N. (2015a). Integrated quay crane and yard truck scheduling for unloading inbound containers. International Journal of Production Economics, 159, 168-177.
  • Kaveshgar, N. ve Huynh, N. (2015b). A genetic algorithm heuristic for solving the quay crane scheduling problem with time windows. Maritime Economics and Logistics, 17, 515-537.
  • Kaveshgar, N., Huynh, N. ve Rahimian, S.K. (2012). An efficient genetic algorithm for solving the quay crane scheduling problem. Expert Systems with Applications, 39, 13108-13117, 2012.
  • Kenan, N. ve Diabat, A. (2015). A branch-and-price algorithm to solve a quay crane scheduling problem. Procedia Computer Science, 61, 527-532.
  • Kim, K.H. ve Park, Y.M. (2004). A crane scheduling method for port container terminals. European Journal of Operational Research, 156, 752-768, 2004.
  • Ku, D. ve Arthanari, T.S. (2014). On double cycling for container port productivity improvement. Annals of Operations Research, 16(1).
  • Lee, C.Y., Liu, M. ve Chu, C. (2014). Optimal algorithm for the general quay crane double-cycling problem. Transportation Science, 49, 957-967.
  • Legato, P. ve Trunfio, R. (2014). A Local branching-based algorithm for the quay crane scheduling problem under unidirectional schedules. Journal of Operation Research, 12, 123-156.
  • Legato, P., Trunfio, R. ve Meisel, F. (2012). Modeling and solving rich quay crane scheduling problems. Computers and Operations Research, 39, 2063-2078.
  • Li, M.W., Hong, W.C., Geng, J. ve Wang, J. (2016). Berth and quay crane coordinated scheduling using multi-objective chaos cloud particle swarm optimization algorithm. Neural Computing and Applications, 20(1).
  • Liang, C.J., Li, M.M., Lu, B., Gu, T., Jo, J. ve Ding, Y. (2015). Dynamic configuration of qc allocating problem based on multi-objective genetic algorithm. Journal of Intelligent Manufacturing, 1-9 (1).
  • Liu, M., Zheng, F ve Li, J. (2015). Scheduling small number of quay cranes with non-interference constraint. Optimization Letters, 9, 403-412.
  • Lu, Z., Han, X., Xi, L. ve Erera, A.L. (2012). A heuristic for the quay crane scheduling problem based on contiguous bay crane operations. Computers and Operations Research, 39, 2915-2928.
  • Meisel, F. ve Bierwirth, C. (2011). A unified approach for the evaluation of quay crane scheduling models and algorithms. Computers & Operations Research, 38, 683–693.
  • Meisel, F. ve Bierwirth, C. (2013). A framework for integrated berth allocation and crane operations planning in seaport container terminals. Transportation Science, 47, 131-147.
  • Nam, H. ve Lee, T. (2013). A scheduling problem for a novel container transport system: A case of mobile harbor operation schedule. Flexible Services and Manufacturing Journal, 25, 576-608.
  • Nguyen, S., Zhang, M., Johnston, M. ve Tan, K.C. (2013). Hybrid evolutionary computation methods for quay crane scheduling problems. Computers & Operations Research, 40, 2083-2093.
  • Rashidi, H. ve Tsang, E.P. (2013). Novel constraints satisfaction models for optimization problems in container terminals. Applied Mathematical Modelling, 37, 3601-3634.
  • Reyes, L.C., Gomez, C., Alvarez, A.L., Valdez, N.R., Castellanos, M.Q., Valdez, G.C. ve Barbosa, J.G. (2016). A hybrid metaheuristic algorithm for the quay crane scheduling problem. Handbook of Research on Military, Aeronautical, and Maritime Logistics and Operations, 238-256, 2016.
  • Rodriguez-Molins, M., Barber, F., Sierra, M.R., Puente, J. ve Salido, M.A. (2012). A genetic algorithm for berth allocation and quay crane assignment. In: Proceedings of Ibero-American Conference on Artificial Intelligence 601-610, Springer Berlin Heidelberg.
  • Rowley, J. ve Slack, F. (2004). Conducting a literature review. Management Research News, 27(6), 31–39.
  • Sammarra, M., Cordeau, J.F., Laporte, G. ve Monaco, M.F. (2007). A tabu search heuristic for the quay crane scheduling problem, Journal of Scheduling, 10, 327–336.
  • Santini, A., Friberg, H.A. ve Ropke, S. (2015). A note on a model for quay crane scheduling with non-crossing constraints. Engineering Optimization, 47, 860-865.
  • Seuring, S. ve Gold, S. (2012). Conducting content-analysis based literature reviews in supply chain management. Supply Chain Management: An International Journal, 17, 544–555.
  • Shin, K. ve Lee, T. (2013). Container loading and unloading scheduling for a mobile harbor system: a global and local search method. Flexible Services and Manufacturing Journal, 25, 557-575.
  • Statheros, T., Howells, G. ve McDonald-Maier, K. (2008). Autonomous ship collision avoidance navigation concepts, technologies and techniques. The Journal of Navigation, 61, 129-142.
  • Tam, C.K., Bucknall, R. ve Greig, A. (2009). Review of collision avoidance and path planning methods for ships in close range encounters. The Journal of Navigation, 62, 455-476.
  • Tang, L., Zhao, J. ve Liu, J. (2014). Modeling and solution of the joint quay crane and truck scheduling problem. European Journal of Operational Research, 236, 978-990.
  • Tavakkoli-Moghaddam, R., Makui, A., Salahi, S., Bazzazi, M. ve Taheri, F. (2009). An efficient algorithm for solving a new mathematical model for a quay crane scheduling problem in container ports. Computer and Industrial Engineering, 56, 241-248.
  • Theodorou, E. ve Diabat, A. (2015). A joint quay crane assignment and scheduling problem: formulation, solution algorithm and computational results. Optimization Letters, 9, 799-817.
  • Tranfield, D., Denyer, D. ve Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14, 207–222.
  • Türkoğulları, Y.B., Taşkın, Z.C., Aras, N. ve Altınel, İ.K. (2014). Optimal berth allocation and time-invariant quay crane assignment in container terminals. European Journal of Operational Research, 235, 88-101.
  • Türkoğulları, Y.B., Taşkın, Z.C., Aras, N. ve Altınel, İ.K. (2016). Optimal berth allocation, time-variant quay crane assignment and scheduling with crane setups in container terminals. European Journal of Operational Research, 254, 985-1001.
  • Ulu, S. ve Akdağ, M. (2015). Dergilerde yayınlanan hakem denetimli makalelerin bibliyometrik profili: Selçuk İletişim örneği. Selçuk Üniversitesi İletişim Fakültesi Dergisi, 9, 5-21.
  • UNCTAD (2016). Review of Maritime Transport, United Nations Conference on Trade and Development.
  • Ünsal, Ö. (2013). Constraint programming approach to quay crane scheduling problem, Yüksek Lisans Tezi, Koç Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  • Ünsal, Ö. ve Oğuz, C. (2013). Constraint programming approach to quay crane scheduling problem. Transportation Research Part E, 59, 108-122.
  • Ursavas, E. (2014). A decision support system for quayside operations in a container terminal. Decision Support Systems, 59, 312-324.
  • Yang, C., Wang, X. ve Li, Z. (2012). An optimization approach for coupling problem of berth allocation and quay crane assignment in container terminal. Computers and Industrial Engineering, 63, 243-253.
  • Zadeh, L.A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.
  • Zeng, Q., Diabat, A. ve Zhang, Q. (2015). A simulation optimization approach for solving the dual-cycling problem in container terminal. Maritime Policy & Management, 42, 806-826.
  • Zhen, L., Yu, S., Wang, S. ve Sun, Z. (2016). Scheduling quay cranes and yard trucks for unloading operations in container ports. Annals and Operation Research, 24(1), 1-24.

KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA

Yıl 2017, Cilt: 9 Sayı: 2, 136 - 161, 01.12.2017
https://doi.org/10.18613/deudfd.351634

Öz

Uluslararası lojistik ve tedarik zinciri sistemi
içinde yer alan limanlar ulaştırma ana faaliyetinin önemli bir halkasını
oluşturmaktadır. Liman operasyonları tüm lojistik süreçlerini doğrudan ve
dolaylı olarak etkilemektedir. Artan limanlar arası rekabet de göz önünde
bulundurulduğunda bu süreçlerin optimal hale getirilmesi gerekliliği ortaya
çıkmaktadır. Özellikle liman operasyonlarında kullanılan rıhtım vinçlerinin
verimliliği liman kapasitesi ve gemilerin limanda bekleme süresi üzerinde
önemli bir etkiye sahiptir. Buradan hareketle, rıhtım vinci operasyonlarından
optimal verim elde edebilmek için birçok model önerilmiştir. Bu çalışmada,
literatürde yer alan konteyner terminallerinde rıhtım vinci çizelgeleme
probleminin çözümüne yönelik önerilen modellerin incelenmesi ve bu modeller
üzerine tartışma yapılması amaçlanmaktadır. Yapılan bibliyometrik analiz
neticesinde, önerilen modellerde kullanılan 21 farklı
çözüm metodu içinde, genetik algoritmanın en sık kullanılan çözüm algoritması
olduğu ortaya çıkmıştır. Yapay zekanın ise en çok tercih edilen yaklaşım tipi
olduğu tespit edilmiştir. Araştırmada ayrıca hızla gelişen teknolojinin
limanların altyapılarını doğrudan etkilediği, limanların daha hızlı elleçleme
yapabilen vinçlere ihtiyaç duyduğu ve bu doğrultuda rıhtım vinci
çizelgelemesine yönelik yenilikçi çözüm modellerinin geliştirilmesi gerektiği
ortaya çıkmıştır.

Kaynakça

  • Al-Dhaheri, N. ve Diabat, A. (2015). The quay crane scheduling problem. Journal of Manufacturing Systems, 36, 87-94.
  • Al-Dhaheri, N. ve Diabat, A. (2016). A Lagrangian relaxation-based heuristic for the multi-ship quay crane scheduling problem with ship stability constraints. Annals and Operation Research, 24 (1).
  • Al-Dhaheri, N., Jebali, A. ve Diabat, A. (2016a). A simulation-based genetic algorithm approach f-for the quay crane scheduling under uncertainty. Simulation Modelling Practice and Theory, 66, 122-138.
  • Al-Dhaheri, N., Jebali, A. ve Diabat, A. (2016b). The quay crane scheduling problem with nonzero crane repositioning time and vessel stability constraints. Computers and Industrial Engineering, 94, 230-244.
  • Aras, N., Türkoğulları, Y., Taşkın, Z.C. ve Altınel, K. (2014). Simultaneous optimization of berth allocation, quay crane assignment and quay crane scheduling problems in container terminals. In: Operations Research Proceedings 2012, Springer International Publishing, 101-107.
  • Beens, M.A. ve Ursavaş, E. (2016). Scheduling cranes at an indented berth. European Journal of Operational Research, 253, 298-313.
  • Bierwirth, C. ve Meisel, F. (2010). A survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operational Research, 202, 615-627.
  • Bierwirth, C. ve Meisel, F. (2015). A follow-up survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operational Research, 244, 675-689.
  • Çağlar, V., Esmer, S. ve Bilgin, A. (2015). Mega konteyner gemilerinin tedarik zinciri ve limanlar üzerindeki etkileri. II. Ulusal Liman Kongresi Bildiriler Kitabı, İzmir.
  • Chen, J.H., Lee, D.H. ve Cao, J.X. (2012). A combinatorial benders’ cuts algorithm for the quayside operation problem at container terminals. Transportation Research Part E: Logistics and Transportation Review, 48, 266-275.
  • Chen, J.H., Lee, D.H. ve Goh, M. (2014). An effective mathematical formulation for the unidirectional cluster-based quay crane scheduling problem. European Journal of Operational Research, 232, 198-208.
  • Chung, S.H. ve Chan, T.S. (2013). A workload balancing genetic algorithm for the quay crane scheduling problem. International Journal of Production Research, 51, 4820-4834.
  • Chung, S.H. ve Choy, K.L. (2012). A modified genetic algorithm for quay crane scheduling operations. Expert Systems with Applications, 39, 4213-4221.
  • Daganzo, C.F. (1989). The crane scheduling problem. Transportation Research Part B: Methodological, 23, 159-175.
  • Davarzani, H., Fahimnia, B., Bell, M. ve Sarkis, J. (2016). Greening ports and maritime logistics: A review. Transportation Research Part D: Transport and Environment, 48, 473-487.
  • Diabat, A. ve Theodorou, E. (2014). An integrated quay crane assignment and scheduling problem. Computers and Industrial Engineering, 73, 115-123.
  • Fu, Y.M. ve Diabat, A. (2015). A Lagrangian relaxation approach for solving the integrated quay crane assignment and scheduling problem. Applied Mathematical Modelling, 39, 1194-1201.
  • Fu, Y.M., Diabat, A. ve Tsai, I.T. (2014). A multi-vessel quay crane assignment and scheduling problem: formulation and heuristic solution approach. Expert Systems with Applications, 41, 6959-6965.
  • Guan, Y., Yang, K.H. ve Zhou, Z. (2013). The crane scheduling problem: models and solution approaches. Annals and Operations Research, 203, 119-139.
  • Guo, P., Cheng, W ve Wang, Y. (2014). A modified generalized extremal optimization algorithm for the quay crane scheduling problem with interference constraints. Engineering Optimization, 46, 1411-1429.
  • Hakam, M.H., Solvang, W.D. ve Hammervoll, T. (2012). A genetic algorithm approach for quay crane scheduling with non-interference constraints at Narvik Container Terminal. International Journal of Logistics: Research and Applications, 15, 269-281.
  • He, J., Huang, Y., Yan, W. ve Wang, S. (2015). Integrated internal truck, yard crane and quay crane scheduling in a container terminal considering energy consumption. Expert System with Applications, 42, 2464-2487.
  • Iris, Ç., Pacino, D., Ropke, S. ve Larsen, A. (2015). Integrated berth allocation and quay crane assignment problem: set partitioning models and computational results. Transportation Research Part E: Logistics and Transportation Review, 81, 75-97.
  • Izquierdo, C.E., Velarde, J.L.G., Batista, B.M. ve Vega, J.M.M. (2013). Hybrid estimation of distribution algorithm for the quay crane scheduling problem. Applied Soft Computing, 13, 4063-4076.
  • Izquierdo, C.E., Ruiz, E.L., Batista, B.M. ve Vega, J.M.M. (2014). A study of rescheduling strategies for the quay crane scheduling problem under random disruptions. Inteligencia Artificial, 54, 35-47.
  • Kaveshgar, N. ve Huynh, N. (2015a). Integrated quay crane and yard truck scheduling for unloading inbound containers. International Journal of Production Economics, 159, 168-177.
  • Kaveshgar, N. ve Huynh, N. (2015b). A genetic algorithm heuristic for solving the quay crane scheduling problem with time windows. Maritime Economics and Logistics, 17, 515-537.
  • Kaveshgar, N., Huynh, N. ve Rahimian, S.K. (2012). An efficient genetic algorithm for solving the quay crane scheduling problem. Expert Systems with Applications, 39, 13108-13117, 2012.
  • Kenan, N. ve Diabat, A. (2015). A branch-and-price algorithm to solve a quay crane scheduling problem. Procedia Computer Science, 61, 527-532.
  • Kim, K.H. ve Park, Y.M. (2004). A crane scheduling method for port container terminals. European Journal of Operational Research, 156, 752-768, 2004.
  • Ku, D. ve Arthanari, T.S. (2014). On double cycling for container port productivity improvement. Annals of Operations Research, 16(1).
  • Lee, C.Y., Liu, M. ve Chu, C. (2014). Optimal algorithm for the general quay crane double-cycling problem. Transportation Science, 49, 957-967.
  • Legato, P. ve Trunfio, R. (2014). A Local branching-based algorithm for the quay crane scheduling problem under unidirectional schedules. Journal of Operation Research, 12, 123-156.
  • Legato, P., Trunfio, R. ve Meisel, F. (2012). Modeling and solving rich quay crane scheduling problems. Computers and Operations Research, 39, 2063-2078.
  • Li, M.W., Hong, W.C., Geng, J. ve Wang, J. (2016). Berth and quay crane coordinated scheduling using multi-objective chaos cloud particle swarm optimization algorithm. Neural Computing and Applications, 20(1).
  • Liang, C.J., Li, M.M., Lu, B., Gu, T., Jo, J. ve Ding, Y. (2015). Dynamic configuration of qc allocating problem based on multi-objective genetic algorithm. Journal of Intelligent Manufacturing, 1-9 (1).
  • Liu, M., Zheng, F ve Li, J. (2015). Scheduling small number of quay cranes with non-interference constraint. Optimization Letters, 9, 403-412.
  • Lu, Z., Han, X., Xi, L. ve Erera, A.L. (2012). A heuristic for the quay crane scheduling problem based on contiguous bay crane operations. Computers and Operations Research, 39, 2915-2928.
  • Meisel, F. ve Bierwirth, C. (2011). A unified approach for the evaluation of quay crane scheduling models and algorithms. Computers & Operations Research, 38, 683–693.
  • Meisel, F. ve Bierwirth, C. (2013). A framework for integrated berth allocation and crane operations planning in seaport container terminals. Transportation Science, 47, 131-147.
  • Nam, H. ve Lee, T. (2013). A scheduling problem for a novel container transport system: A case of mobile harbor operation schedule. Flexible Services and Manufacturing Journal, 25, 576-608.
  • Nguyen, S., Zhang, M., Johnston, M. ve Tan, K.C. (2013). Hybrid evolutionary computation methods for quay crane scheduling problems. Computers & Operations Research, 40, 2083-2093.
  • Rashidi, H. ve Tsang, E.P. (2013). Novel constraints satisfaction models for optimization problems in container terminals. Applied Mathematical Modelling, 37, 3601-3634.
  • Reyes, L.C., Gomez, C., Alvarez, A.L., Valdez, N.R., Castellanos, M.Q., Valdez, G.C. ve Barbosa, J.G. (2016). A hybrid metaheuristic algorithm for the quay crane scheduling problem. Handbook of Research on Military, Aeronautical, and Maritime Logistics and Operations, 238-256, 2016.
  • Rodriguez-Molins, M., Barber, F., Sierra, M.R., Puente, J. ve Salido, M.A. (2012). A genetic algorithm for berth allocation and quay crane assignment. In: Proceedings of Ibero-American Conference on Artificial Intelligence 601-610, Springer Berlin Heidelberg.
  • Rowley, J. ve Slack, F. (2004). Conducting a literature review. Management Research News, 27(6), 31–39.
  • Sammarra, M., Cordeau, J.F., Laporte, G. ve Monaco, M.F. (2007). A tabu search heuristic for the quay crane scheduling problem, Journal of Scheduling, 10, 327–336.
  • Santini, A., Friberg, H.A. ve Ropke, S. (2015). A note on a model for quay crane scheduling with non-crossing constraints. Engineering Optimization, 47, 860-865.
  • Seuring, S. ve Gold, S. (2012). Conducting content-analysis based literature reviews in supply chain management. Supply Chain Management: An International Journal, 17, 544–555.
  • Shin, K. ve Lee, T. (2013). Container loading and unloading scheduling for a mobile harbor system: a global and local search method. Flexible Services and Manufacturing Journal, 25, 557-575.
  • Statheros, T., Howells, G. ve McDonald-Maier, K. (2008). Autonomous ship collision avoidance navigation concepts, technologies and techniques. The Journal of Navigation, 61, 129-142.
  • Tam, C.K., Bucknall, R. ve Greig, A. (2009). Review of collision avoidance and path planning methods for ships in close range encounters. The Journal of Navigation, 62, 455-476.
  • Tang, L., Zhao, J. ve Liu, J. (2014). Modeling and solution of the joint quay crane and truck scheduling problem. European Journal of Operational Research, 236, 978-990.
  • Tavakkoli-Moghaddam, R., Makui, A., Salahi, S., Bazzazi, M. ve Taheri, F. (2009). An efficient algorithm for solving a new mathematical model for a quay crane scheduling problem in container ports. Computer and Industrial Engineering, 56, 241-248.
  • Theodorou, E. ve Diabat, A. (2015). A joint quay crane assignment and scheduling problem: formulation, solution algorithm and computational results. Optimization Letters, 9, 799-817.
  • Tranfield, D., Denyer, D. ve Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14, 207–222.
  • Türkoğulları, Y.B., Taşkın, Z.C., Aras, N. ve Altınel, İ.K. (2014). Optimal berth allocation and time-invariant quay crane assignment in container terminals. European Journal of Operational Research, 235, 88-101.
  • Türkoğulları, Y.B., Taşkın, Z.C., Aras, N. ve Altınel, İ.K. (2016). Optimal berth allocation, time-variant quay crane assignment and scheduling with crane setups in container terminals. European Journal of Operational Research, 254, 985-1001.
  • Ulu, S. ve Akdağ, M. (2015). Dergilerde yayınlanan hakem denetimli makalelerin bibliyometrik profili: Selçuk İletişim örneği. Selçuk Üniversitesi İletişim Fakültesi Dergisi, 9, 5-21.
  • UNCTAD (2016). Review of Maritime Transport, United Nations Conference on Trade and Development.
  • Ünsal, Ö. (2013). Constraint programming approach to quay crane scheduling problem, Yüksek Lisans Tezi, Koç Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  • Ünsal, Ö. ve Oğuz, C. (2013). Constraint programming approach to quay crane scheduling problem. Transportation Research Part E, 59, 108-122.
  • Ursavas, E. (2014). A decision support system for quayside operations in a container terminal. Decision Support Systems, 59, 312-324.
  • Yang, C., Wang, X. ve Li, Z. (2012). An optimization approach for coupling problem of berth allocation and quay crane assignment in container terminal. Computers and Industrial Engineering, 63, 243-253.
  • Zadeh, L.A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.
  • Zeng, Q., Diabat, A. ve Zhang, Q. (2015). A simulation optimization approach for solving the dual-cycling problem in container terminal. Maritime Policy & Management, 42, 806-826.
  • Zhen, L., Yu, S., Wang, S. ve Sun, Z. (2016). Scheduling quay cranes and yard trucks for unloading operations in container ports. Annals and Operation Research, 24(1), 1-24.
Toplam 67 adet kaynakça vardır.

Ayrıntılar

Bölüm Makaleler
Yazarlar

Remzi Fışkın

Fevzi Bitiktaş

Yayımlanma Tarihi 1 Aralık 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 9 Sayı: 2

Kaynak Göster

APA Fışkın, R., & Bitiktaş, F. (2017). KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 9(2), 136-161. https://doi.org/10.18613/deudfd.351634
AMA Fışkın R, Bitiktaş F. KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi. Aralık 2017;9(2):136-161. doi:10.18613/deudfd.351634
Chicago Fışkın, Remzi, ve Fevzi Bitiktaş. “KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA”. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 9, sy. 2 (Aralık 2017): 136-61. https://doi.org/10.18613/deudfd.351634.
EndNote Fışkın R, Bitiktaş F (01 Aralık 2017) KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 9 2 136–161.
IEEE R. Fışkın ve F. Bitiktaş, “KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA”, Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, c. 9, sy. 2, ss. 136–161, 2017, doi: 10.18613/deudfd.351634.
ISNAD Fışkın, Remzi - Bitiktaş, Fevzi. “KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA”. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 9/2 (Aralık 2017), 136-161. https://doi.org/10.18613/deudfd.351634.
JAMA Fışkın R, Bitiktaş F. KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi. 2017;9:136–161.
MLA Fışkın, Remzi ve Fevzi Bitiktaş. “KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA”. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, c. 9, sy. 2, 2017, ss. 136-61, doi:10.18613/deudfd.351634.
Vancouver Fışkın R, Bitiktaş F. KONTEYNER TERMİNALLERİNDE RIHTIM VİNCİ ÇİZELGELEME PROBLEMİNİN ÇÖZÜMÜNE YÖNELİK ÖNERİLEN MODELLER ÜZERİNE BİR ARAŞTIRMA. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi. 2017;9(2):136-61.

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