Mathematical Model for Ship Berthing Allocation in A Multipurpose Terminal: Study Case from Tanjung Perak Port Indonesia

Maulana Yafie Danendra; Setyo Nugroho; Achmad Mustakim

doi:10.12962/j25481479.v9i2.20280

Mathematical Model for Ship Berthing Allocation in A Multipurpose Terminal: Study Case from Tanjung Perak Port Indonesia

Maulana Yafie Danendra, Setyo Nugroho, Achmad Mustakim

Abstract

In the operation of a multipurpose terminal in a port (terminal that can serve and be berthed to more than one type of a ship), the position of planning an optimal berth allocation for ships is essential to maintain. Berth allocation planning (BAP) is considered tactical planning that can impact the performance of a terminal and the cost of a ship in a port. That is because the longer the waiting time of a ship that waits to be berthed, the smaller number of ships will be served by the terminal, and the higher the cost will be borne by the ships. This paper, based on a case study in Terminal Jamrud of Tanjung Perak Port of Indonesia, will discuss a Mixed Integer Linear Programming (MILP) mathematical model of a BAP to minimize the ships’ waiting time to berth with consideration to the tailored conditions of the multipurpose terminal. The results show that the optimization model yielded reductions in the datasets 1 to 3 tested on the North/West and 4 to 6 on the South pier. There are savings in the waiting time reduced in hours, which are 403 (12,82%), 189 (26,18%), 418 (30,74%) for the North/West pier and 34 (16,43%), 1663 (88,13%), 475 (46,75%) for the South pier.

Keywords

Berth Allocation Planning, Optimization, MILP, Multipurpose Terminal.

Full Text:

PDF

References

B. Triatmodjo, Perencanaan Pelabuhan. Yogyakarta: Beta Offset, 2009.

UNCTAD, “Review of Maritime Transport.”

A. K. Putra, “Analisis Kinerja Pelayanan Bongkar Muat Pada Terminal Jamrud Berdasarkan Model Sistem Antrian (Studi Kasus Pada Terminal Jamrud PT. Pelabuhan Indonesia III (Persero) Cabang Tanjung Perak),” Malang, 2016.

D. Steenken, S. Voß, and R. Stahlbock, “Container terminal operation and operations research - A classification and literature review,” OR Spectrum, vol. 26, no. 1. pp. 3–49, 2004. doi: 10.1007/s00291-003-0157-z.

R. Moorthy and C. P. Teo, “Berth management in container terminal: The template design problem,” OR Spectrum, vol. 28, no. 4, pp. 495–518, Oct. 2006, doi: 10.1007/s00291-006-0036-5.

F. Rodrigues and A. Agra, “Berth allocation and quay crane assignment/scheduling problem under uncertainty: A survey,” European Journal of Operational Research, vol. 303, no. 2. Elsevier B.V., pp. 501–524, Dec. 01, 2022. doi: 10.1016/j.ejor.2021.12.040.

C. Bierwirth and F. Meisel, “A survey of berth allocation and quay crane scheduling problems in container terminals,” Eur J Oper Res, vol. 202, no. 3, pp. 615–627, May 2010, doi: 10.1016/j.ejor.2009.05.031.

N. Umang and M. Bierlaire, “The berth allocation problem in bulk ports,” 2011.

V. H. Barros, T. S. Costa, A. C. M. Oliveira, and L. A. N. Lorena, “Model and heuristic for berth allocation in tidal bulk ports with stock level constraints,” Comput Ind Eng, vol. 60, no. 4, pp. 606–613, May 2011, doi: 10.1016/j.cie.2010.12.018.

A. T. Ernst, C. Oğuz, G. Singh, and G. Taherkhani, “Mathematical models for the berth allocation problem in dry bulk terminals,” Journal of Scheduling, vol. 20, no. 5, pp. 459–473, Oct. 2017, doi: 10.1007/s10951-017-0510-8.

N. Cheimanoff, F. Fontane, M. N. Kitri, and N. Tchernev, “A reduced VNS based approach for the dynamic continuous berth allocation problem in bulk terminals with tidal constraints,” Expert Syst Appl, vol. 168, Apr. 2021, doi: 10.1016/j.eswa.2020.114215.

I. B. G. Rodrigues, R. De Alvarenga Rosa, T. C. Gomes, and G. M. Ribeiro, “Mathematical model for the Berth Allocation Problem in ports with cargo operation limitations along the pier,” Gestao e Producao, vol. 23, no. 4, pp. 771–786, Oct. 2016, doi: 10.1590/0104-530X2266-15.

C. Bierwirth and F. Meisel, “A follow-up survey of berth allocation and quay crane scheduling problems in container terminals,” European Journal of Operational Research, vol. 244, no. 3. Elsevier B.V., pp. 675–689, Aug. 01, 2015. doi: 10.1016/j.ejor.2014.12.030.

J. L. M. de Andrade and G. C. Menezes, “A column generation-based heuristic to solve the integrated planning, scheduling, yard allocation and berth allocation problem in bulk ports,” Journal of Heuristics, vol. 29, no. 1, pp. 39–76, Feb. 2023, doi: 10.1007/s10732-022-09506-3.

K. Huang, Suprayogi, and Ariantini, “A continuous berth template design model with multiple wharfs,” Maritime Policy & Management, vol. 43, no. 6, pp. 763–775, Aug. 2016, doi: 10.1080/03088839.2016.1169449.

R. T. Cahyono, E. J. Flonk, and B. Jayawardhana, “Dynamic berth and quay crane allocation for multiple berth positions and quay cranes,” in 2015 European Control Conference (ECC), IEEE, Jul. 2015, pp. 3262–3267. doi: 10.1109/ECC.2015.7331037.

R. T. Cahyono, E. J. Flonk, and B. Jayawardhana, “Discrete-Event Systems Modeling and the Model Predictive Allocation Algorithm for Integrated Berth and Quay Crane Allocation,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 3, pp. 1321–1331, Mar. 2020, doi: 10.1109/TITS.2019.2910283.

V. K. Ladesi, K. Verawati, and H. D. Hamidi, “Preliminary study for berth allocation problem under uncertainty at PT Mustika Alam Lestari (MAL) port of Tanjung Priok, Jakarta,” 2023, p. 050062. doi: 10.1063/5.0129643.

D. N. Prayogo, K. Komarudin, A. Hidayatno, and A. Mubarak, “Bi-objective Recoverable Berth Allocation and Quay Crane Assignment Planning under Environmental Uncertainty,” International Journal of Technology, vol. 13, no. 3, p. 677, Jul. 2022, doi: 10.14716/ijtech.v13i3.5269.

V. K. Ladesi and J. Amiruddin, “Risk management approach to solve berth allocation problem (BAP) in port,” 2023, p. 050063. doi: 10.1063/5.0129650.

J. F. Cordeau, G. Laporte, P. Legato, and L. Moccia, “Models and tabu search heuristics for the berth-allocation problem,” Transportation Science, vol. 39, no. 4, pp. 526–538, 2005, doi: 10.1287/trsc.1050.0120.

DOI: http://dx.doi.org/10.12962/j25481479.v9i2.20280