برنامه‌ریزی عملیات جانب دریا با استفاده از الگوریتم بهینه‌سازی ازدحام ذرات تکاملی

نوع مقاله : علمی - پژوهشی

نویسندگان
1 دانش آموخته کارشناسی ارشد، دانشکده مهندسی عمران، برنامه ریزی حمل و نقل، دانشگاه علم و صنعت ایران، تهران، ایران
2 استادیار گروه برنامه ریزی حمل و نقل، دانشکده مهندسی عمران، برنامه ریزی حمل و نقل، دانشگاه علم و صنعت ایران، تهران، ایران
چکیده
مسائل عملیات جانب دریا در پایانه‌های کانتینری شامل سه مسئله می‌شوند؛ مسئله تخصیص پهلوگاه، مسئله تخصیص جرثقیل اسکله و مسئله برنامه‌ریزی جرثقیل اسکله. مقاله حاضر هر سه مسئله عملیات جانب دریا را به‌صورت ادغامی و در دو مرحله حل می‌کند. در مرحله اول دو مسئله تخصیص پهلوگاه و تخصیص جرثقیل اسکله در یک مدل ریاضی مدل‌سازی و حل می‌شوند. در مرحله دوم، مسئله برنامه‌ریزی جرثقیل اسکله در یک مدل ریاضی جداگانه مدل‌سازی و با کمک الگوریتم ابتکاری برنامه‌ریزی پویا حل می‌شود. با توجه به NP-Hard بودن مسائل عملیات جانب دریا، از الگوریتم‌های ابتکاری/فراابتکاری برای حل آن‌ها استفاده می‌شود. مقاله حاضر برای اولین بار از نسخه تکاملی الگوریتم بهینه‌سازی ازدحام ذرات (EPSO) برای حل مسائل عملیات جانب دریا استفاده کرده است. برای مقایسه عملکرد این الگوریتم، نتایج آن با نتایج نسخه اولیه همان الگوریتم (PSO) و الگوریتم ژنتیک(GA) مقایسه می‌شود. نتایج عددی این مقاله نشان می‌دهد که الگوریتم EPSO، تقریباً پاسخ‌هایی مشابه با الگوریتم GA (با 1% اختلاف) دارد؛ اما ازنظر زمان اجرا، سرعت بیشتری نسبت به الگوریتم GA دارد. در مقایسه با الگوریتم PSO، حدود 6%، پاسخ‌های بهتری گزارش می‌دهد اما ازنظر زمان اجرا، اندکی آهسته‌تر عمل می‌کند. اعتبارسنجی مقاله حاضر با داده‌های واقعی ورود و خروج کشتی‌ها در هر دو پایانه کانتینری بندر شهید رجایی انجام گرفته است.

کلیدواژه‌ها


عنوان مقاله English

Seaside Operation Planning with Evolutionary Particle Swarm Optimization Algorithm

نویسندگان English

Ali Omidvarvarpanah Ahmadabadi 1
Abdolreza Sheikholeslami 2
1 Master of science, Transportation Planning, School of civil engineering, Iran University of Science and Technology, Tehran, Iran
2 assistant Professor, Department of transportation Planning, School of civil engineering, Iran University of Science and Technology, Tehran, Iran
چکیده English

One of the port planning problems that has been noticed in many papers and research is the berth planning problems. Berth planning includes two sub-problems; Berth Allocation Problem (BAP) and Quay Crane Assignment Problem (QCAP). This paper develops one mathematical model by integrating these two sub-problems. The berth allocation and quay crane assignment model (BAQCAP) is solved by two metaheuristic algorithms; Taboo Search (TS) and Ant Colony Optimization (ACO). On the other hand, the berth plan is located in a disturbed environment; unexpected events may occur during the execution of the plan, making it infeasible or challenging to do the initial berth plan. These unexpected events are known as disruptions, which can impose additional costs on the port or make the initial berth plan infeasible. For this reason, The primary purpose of this paper is on the berth plan recovery in the disrupted situation. the Berth plan is recovered with two methods; Global recovery and local recovery. This paper compares global and local recovery to identify the optimal method for berth plan recovery. The numerical results show the optimal performance in the local recovery method. In this paper, the data from Shahid Rajaei port is used.

کلیدواژه‌ها English

Seaside Operation
Berth Allocation Problem (BAP)
Quay Crane Assignment Problem (QCAP)
Quay Crane Scheduling Problem (QCSP)
Evolutionary Particle Swarm Optimization (EPSO)
  • Agra, A. and M. Oliveira (2018). "MIP approaches for the integrated berth allocation and quay crane assignment and scheduling problem." European Journal of Operational Research 264(1): 138-148.

 

  • Al-Dhaheri, N. and A. Diabat (2017). "A Lagrangian relaxation-based heuristic for the multi-ship quay crane scheduling problem with ship stability constraints." Annals of Operations Research 248(1-2): 1-24.

 

  • Bierwirth, C. and F. Meisel (2010). "A survey of berth allocation and quay crane scheduling problems in container terminals." European Journal of Operational Research 202(3): 615-627.

 

  • Bierwirth, C. and F. Meisel (2015). "A follow-up survey of berth allocation and quay crane scheduling problems in container terminals." European Journal of Operational Research 244(3): 675-689.

 

  • Chang, D., Z. Jiang, W. Yan and J. He (2010). "Integrating berth allocation and quay crane assignments." Transportation Research Part E: Logistics and Transportation Review 46(6): 975-990.

 

  • Correcher, J. F., R. Alvarez-Valdes and J. M. Tamarit (2019). "New exact methods for the time-invariant berth allocation and quay crane assignment problem." European Journal of Operational Research 275(1): 80-92.

 

  • Daganzo, C. F. (1989). "The crane scheduling problem." Transportation Research Part B: Methodological 23(3): 159-175.

 

  • Diabat, A. and E. Theodorou (2014). "An integrated quay crane assignment and scheduling problem." Computers & Industrial Engineering 73: 115-123.

 

  • Han, X., X. Gong and J. Jo (2015). "A new continuous berth allocation and quay crane assignment model in container terminal." Computers & Industrial Engineering 89: 15-22.

 

  • Hsu, H.-P., T.-L. Chiang, C.-N. Wang, H.-P. Fu and C.-C. Chou (2019). "A hybrid GA with variable quay crane assignment for solving berth allocation problem and quay crane assignment problem simultaneously." Sustainability 11(7): 2018.

 

  • Ilati, G., A. Sheikholeslami and E. Hassannayebi (2014). "A simulation-based optimization approach for integrated port resource allocation problem." PROMET-Traffic&Transportation 26(3): 243-255.

 

  • Iris, Ç., D. Pacino and S. Ropke (2017). "Improved formulations and an adaptive large neighborhood search heuristic for the integrated berth allocation and quay crane assignment problem." Transportation Research Part E: Logistics and Transportation Review 105: 123-147.

 

  • Iris, Ç., D. Pacino, S. Ropke and A. Larsen (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.
  • Lalla-Ruiz, E., J. L. González-Velarde, B. Melián-Batista and J. M. Moreno-Vega (2014). "Biased random key genetic algorithm for the tactical berth allocation problem." Applied Soft Computing 22: 60-76.

 

  • Lee, D.-H. and H. Qiu Wang (2010). "Integrated discrete berth allocation and quay crane scheduling in port container terminals." Engineering Optimization 42(8): 747-761.

 

  • Liu, C., L. Zheng and C. Zhang (2016). "Behavior perception-based disruption models for berth allocation and quay crane assignment problems." Computers & Industrial Engineering 97: 258-275.

 

  • Lujan, E., E. Vergara, J. Rodriguez-Melquiades, M. Jiménez-Carrión, C. Sabino-Escobar and F. Gutierrez (2021). "A Fuzzy Optimization Model for the Berth Allocation Problem and Quay Crane Allocation Problem (BAP+ QCAP) with n Quays." Journal of Marine Science and Engineering 9(2): 152.

 

  • Malekahmadi, A., M. Alinaghian, S. R. Hejazi and M. A. A. Saidipour (2020). "Integrated continuous berth allocation and quay crane assignment and scheduling problem with time-dependent physical constraints in container terminals." Computers & Industrial Engineering 147: 106672.

 

  • Meisel, F. and C. Bierwirth (2013). "A framework for integrated berth allocation and crane operations planning in seaport container terminals." Transportation Science 47(2): 131-147.

 

  • Miranda, V. and N. Fonseca (2002). New evolutionary particle swarm algorithm (EPSO) applied to voltage/VAR control. in Proc. 14th Power Syst. Comput. Conf, Citeseer.
  • Park, Y.-M. and K. H. Kim (2003). "A scheduling method for Berth and Quay cranes." OR Spectrum 25(1): 1-23.

 

  • Poli, R., J. Kennedy and T. Blackwell (2007). "Particle swarm optimization." Swarm intelligence 1(1): 33-57.

 

  • Rodrigues, F. and A. Agra (2021). "An exact robust approach for the integrated berth allocation and quay crane scheduling problem under uncertain arrival times." European Journal of Operational Research.

 

  • Sirimanne, S. N., J. Hoffman, W. Juan, R. Asariotis, M. Assaf, G. Ayala, H. Benamara, D. Chantrel, J. Hoffmann and A. Premti (2019). Review of maritime transport 2019, tech. rep.

 

  • Theodorou, E. and A. Diabat (2015). "A joint quay crane assignment and scheduling problem: formulation, solution algorithm and computational results." Optimization Letters 9(4): 799-817.

 

  • Türkoğulları, Y. B., Z. C. Taşkın, N. Aras and İ. K. Altınel (2014). "Optimal berth allocation and time-invariant quay crane assignment in container terminals." European Journal of Operational Research 235(1): 88-101.

 

  • Türkoğulları, Y. B., Z. C. Taşkın, N. Aras and İ. K. Altınel (2016). "Optimal berth allocation, time-variant quay crane assignment and scheduling with crane setups in container terminals." European Journal of Operational Research 254(3): 985-1001.

 

  • Unsal, O. and C. Oguz (2013). "Constraint programming approach to quay crane scheduling problem." Transportation Research Part E: Logistics and Transportation Review 59: 108-122.

 

  • Ursavas, E. (2014). "A decision support system for quayside operations in a container terminal." Decision Support Systems 59: 312-324.

 

  • Vacca, I., M. Salani and M. Bierlaire (2013). "An exact algorithm for the integrated planning of berth allocation and quay crane assignment." Transportation Science 47(2): 148-161.

 

  • Wawrzyniak, J., M. Drozdowski and É. Sanlaville (2020). "Selecting algorithms for large berth allocation problems." European Journal of Operational Research 283(3): 844-862.

 

  • Xiang, X. and C. Liu (2021). "An almost robust optimization model for integrated berth allocation and quay crane assignment problem." Omega: 102455.

 

  • Zeng, Q., Z. Yang and X. Hu (2011). "Disruption recovery model for berth and quay crane scheduling in container terminals." Engineering Optimization 43(9): 967-983.

 

  • تاریخ دریافت 22 آبان 1400
  • تاریخ بازنگری 08 دی 1400
  • تاریخ پذیرش 11 دی 1400