Publication

Discrete-event systems modeling and model predictive allocation algorithm for integrated berth and quay crane allocation

Tri Cahyono, R., Flonk, E. & Jayawardhana, B., 2019, In : Ieee transactions on intelligent transportation systems. p. 1-11

Research output: Contribution to journalArticleAcademicpeer-review

APA

Tri Cahyono, R., Flonk, E., & Jayawardhana, B. (2019). Discrete-event systems modeling and model predictive allocation algorithm for integrated berth and quay crane allocation. Ieee transactions on intelligent transportation systems, 1-11. https://doi.org/10.1109/TITS.2019.2910283

Author

Tri Cahyono, Rully ; Flonk, Engel ; Jayawardhana, Bayu. / Discrete-event systems modeling and model predictive allocation algorithm for integrated berth and quay crane allocation. In: Ieee transactions on intelligent transportation systems. 2019 ; pp. 1-11.

Harvard

Tri Cahyono, R, Flonk, E & Jayawardhana, B 2019, 'Discrete-event systems modeling and model predictive allocation algorithm for integrated berth and quay crane allocation', Ieee transactions on intelligent transportation systems, pp. 1-11. https://doi.org/10.1109/TITS.2019.2910283

Standard

Discrete-event systems modeling and model predictive allocation algorithm for integrated berth and quay crane allocation. / Tri Cahyono, Rully; Flonk, Engel; Jayawardhana, Bayu.

In: Ieee transactions on intelligent transportation systems, 2019, p. 1-11.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Tri Cahyono R, Flonk E, Jayawardhana B. Discrete-event systems modeling and model predictive allocation algorithm for integrated berth and quay crane allocation. Ieee transactions on intelligent transportation systems. 2019;1-11. https://doi.org/10.1109/TITS.2019.2910283


BibTeX

@article{83bf867f6ba84a81baaac51088c101e8,
title = "Discrete-event systems modeling and model predictive allocation algorithm for integrated berth and quay crane allocation",
abstract = "In this paper, we study the problem of integrated berth and quay crane allocation (I-BCAP) in general seaport container terminals and propose model predictive allocation (MPA) algorithm and preconditioning methods for solving I-BCAP. Firstly, we propose a dynamical modeling framework based on discrete-event systems (DES) that describes the operation of berthing process with multiple discrete berthing positions and multiple quay cranes. Secondly, based on the discrete-event model, we propose a MPA algorithm for solving I-BCAP using model predictive control (MPC) principle with a rolling event horizon. The validation and performance evaluation of the proposed modeling framework and allocation method are done using: (i). extensive Monte-Carlo simulations with realistically-generated datasets; (ii). real dataset from a container terminal in Tanjung Priuk port, located in Jakarta, Indonesia; and (iii). real life field experiment at the aforementioned container terminal. The numerical simulation results show that our proposed MPA algorithm can improve the efficiency of the process where the total handling and waiting cost is reduced by approximately 6 - 9{\%} in comparison to the commonly adapted method of first-come first-served (FCFS) (for the berthing process) combined with the density-based quay cranes allocation (DBQA) strategy. Moreover, the proposed method outperforms the state-of-the-art HPSO-based and GA-based method proposed in recent literature. The real life field experiment shows an improvement of about 6{\%} in comparison to the existing allocation method used in the terminal.",
author = "{Tri Cahyono}, Rully and Engel Flonk and Bayu Jayawardhana",
year = "2019",
doi = "10.1109/TITS.2019.2910283",
language = "English",
pages = "1--11",
journal = "Ieee transactions on intelligent transportation systems",
issn = "1524-9050",
publisher = "IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC",

}

RIS

TY - JOUR

T1 - Discrete-event systems modeling and model predictive allocation algorithm for integrated berth and quay crane allocation

AU - Tri Cahyono, Rully

AU - Flonk, Engel

AU - Jayawardhana, Bayu

PY - 2019

Y1 - 2019

N2 - In this paper, we study the problem of integrated berth and quay crane allocation (I-BCAP) in general seaport container terminals and propose model predictive allocation (MPA) algorithm and preconditioning methods for solving I-BCAP. Firstly, we propose a dynamical modeling framework based on discrete-event systems (DES) that describes the operation of berthing process with multiple discrete berthing positions and multiple quay cranes. Secondly, based on the discrete-event model, we propose a MPA algorithm for solving I-BCAP using model predictive control (MPC) principle with a rolling event horizon. The validation and performance evaluation of the proposed modeling framework and allocation method are done using: (i). extensive Monte-Carlo simulations with realistically-generated datasets; (ii). real dataset from a container terminal in Tanjung Priuk port, located in Jakarta, Indonesia; and (iii). real life field experiment at the aforementioned container terminal. The numerical simulation results show that our proposed MPA algorithm can improve the efficiency of the process where the total handling and waiting cost is reduced by approximately 6 - 9% in comparison to the commonly adapted method of first-come first-served (FCFS) (for the berthing process) combined with the density-based quay cranes allocation (DBQA) strategy. Moreover, the proposed method outperforms the state-of-the-art HPSO-based and GA-based method proposed in recent literature. The real life field experiment shows an improvement of about 6% in comparison to the existing allocation method used in the terminal.

AB - In this paper, we study the problem of integrated berth and quay crane allocation (I-BCAP) in general seaport container terminals and propose model predictive allocation (MPA) algorithm and preconditioning methods for solving I-BCAP. Firstly, we propose a dynamical modeling framework based on discrete-event systems (DES) that describes the operation of berthing process with multiple discrete berthing positions and multiple quay cranes. Secondly, based on the discrete-event model, we propose a MPA algorithm for solving I-BCAP using model predictive control (MPC) principle with a rolling event horizon. The validation and performance evaluation of the proposed modeling framework and allocation method are done using: (i). extensive Monte-Carlo simulations with realistically-generated datasets; (ii). real dataset from a container terminal in Tanjung Priuk port, located in Jakarta, Indonesia; and (iii). real life field experiment at the aforementioned container terminal. The numerical simulation results show that our proposed MPA algorithm can improve the efficiency of the process where the total handling and waiting cost is reduced by approximately 6 - 9% in comparison to the commonly adapted method of first-come first-served (FCFS) (for the berthing process) combined with the density-based quay cranes allocation (DBQA) strategy. Moreover, the proposed method outperforms the state-of-the-art HPSO-based and GA-based method proposed in recent literature. The real life field experiment shows an improvement of about 6% in comparison to the existing allocation method used in the terminal.

U2 - 10.1109/TITS.2019.2910283

DO - 10.1109/TITS.2019.2910283

M3 - Article

SP - 1

EP - 11

JO - Ieee transactions on intelligent transportation systems

JF - Ieee transactions on intelligent transportation systems

SN - 1524-9050

ER -

ID: 77534198