Monte-Carlo analysis model for evaluation of container terminal parameters
https://doi.org/10.21821/2309-5180-2024-16-6-837-846
Abstract
This paper considers using Monte-Carlo analysis method for evaluation some of the parameters of a container terminal. A high amount of scientific work on this topic is noted in domestic literature. International scientific literature concerning usage of Monte-Carlo method for simulating different parameters of container terminals is also analyzed. We note that foreign authors often use Monte-Carlo analysis as an auxiliary method, for example, for checking results of discrete-event simulation model of a complicated logistical system for adequacy, whereas domestic authors often use Monte-Carlo analysis as a method for direct evaluation of container or other cargo terminals parameters. This study proposes a variant of a model for evaluating the necessary container yard capacity, its area and berth utilization of a container terminal, using Monte-Carlo analysis method. We develop a model based on analytical formulas, where some initial parameters take form of probabilistic distributions, rather than determined values. Such parameters are expected cargo turnover, vessel handling equipment productivity and container dwell times. It should be noted that all these parameters can be preliminarily evaluated by port designers, investors or cargo terminal operators. We show an example of model calculations using Monte-Carlo analysis method and some values of initial parameters. Observed results are adequate for a model of such scope as it shows, for example, that most expected value of berth utilization becomes lower as the number of berths becomes larger.
About the Authors
A. V. GalinRussian Federation
Galin, Aleksandr V. — Dr. of Technical Sciences, professor
5/7 Dvinskaya Str., St. Petersburg, 198035
P. S. Rudny
Russian Federation
Rudny, Pavel S. — Postgraduate Supervisor
5/7 Dvinskaya Str., St. Petersburg, 198035
K. A. Galin
Russian Federation
Galin, Kirill А. — engineer
30/32 Griboedov canal emb., St. Petersburg, 191023
References
1. H. Agerschou [et al.]. Planning and design of ports and marine terminals. London: Thomas Telford Publishing, 2004.
2. O. A. Izotov, A. V. Gultyaev “Otsenka trebuemykh tekhnologicheskikh resursov putem statisticheskogo modelirovaniya.” Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota im. admirala S. O. Makarova 10.3 (2018): 497‒506. DOI: 10.21821/2309-5180-2018-10-3-497-506.
3. A. L. Kuznetsov, A. V. Kirichenko, A. D. Semenov “Analiticheskoe utochnenie metoda statisticheskikh ispytanij dlya issledovaniya morskikh portov.” Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota im. admirala S. O. Makarova 14.6 (2022): 905‒914. DOI: 10.21821/2309-5180-2022-14-6-905-914.
4. A. L. Kuznetsov, A. Z. Borevich, A. A. Radchenko “Strategiya upravleniya shtabelem kontejnernogo terminala.” Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota im. admirala S. O. Makarova 12.5 (2020): 853‒860. DOI: 10.21821/2309-5180-2020-12-5-853-860.
5. Junior, I. C. L., de Oliveira, U. R., de Almeida Guimarães, V., Ribeiro, L. G., & Fernandes, V. A. “Probabilistic analysis of the sustainable performance of container terminals.” Research in Transportation Business & Management 43 (2022): 100725.
6. Alali, Kareem, and Ammar Al-Bazi. “Management of Container Terminal Operations Using Monte Carlo Simulation.” OR55 Annual Conference (2013): 115–121.
7. Cahyono, Rully Tri, Saskia Puspa Kenaka, and Bayu Jayawardhana. “Simultaneous allocation and scheduling of quay cranes, yard cranes, and trucks in dynamical integrated container terminal operations.” IEEE Transactions on Intelligent Transportation Systems 23.7 (2021): 8564–8578.
8. Nourmohammadzadeh, Abtin, and Stefan Voß. “A robust multiobjective model for the integrated berth and quay crane scheduling problem at seaside container terminals.” Annals of Mathematics and Artificial Intelligence 90.7 (2022): 831–853.
9. Xuan, Beng, et al. “Monte Carlo Tree Search algorithm for the receiving containers intelligently problem among container shipping terminals.” Journal of Computational Methods in Sciences and Engineering 22.1 (2022): 89–96.
Review
For citations:
Galin A.V., Rudny P.S., Galin K.A. Monte-Carlo analysis model for evaluation of container terminal parameters. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova. 2024;16(6):837-846. (In Russ.) https://doi.org/10.21821/2309-5180-2024-16-6-837-846