Simulation and optimization of the cargo terminal in the AnyLogic environment

Mokshin, Vladimir; Кирпичников, А П; Soiko, A. I.

doi:10.1088/1742-6596/1368/4/042082

Cited by 4 publications

(3 citation statements)

References 18 publications

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“…For developing passenger flow or queuing models we can use the following programs: AnyLogic, Arena, Bizagi Modeler, Business Studio, Enterprise Dynamics, ExtendSim, Flexsim, GPSS W, Plant Simulation, Process Simulator, Rand Model Designer, Simio Simul8 [34]. Comparisons for these simulation programs have been made by Yakimov et al [35].…”

Section: Software Selectionmentioning

confidence: 99%

Study on the Impact of Health Condition Registration and Temperature Check on Inbound Passenger Flow and Optimisation Measures in a Metro Station during the COVID-19 Pandemic

Yu,

2023

PROMTT

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The Guangzhou Metro Authority implemented health condition registration and temperature checks to curb the spread of the virus during the COVID-19 pandemic. However, it is important to investigate how these measures may have impacted the get-through efficiency and whether they caused the increased crowding at entrances and the station hall. To address these questions, simulation models based on the T Station were developed using AnyLogic. The model compared the get-through efficiencies with and without the anti-epidemic measures, while also analysing the risk of crowding at entrances and within the station hall after their implementation. Results revealed an increase in the number of passengers unsuccessfully passing through the check-in gate machines from 15% to 53% within 5 minutes, and 10% to 45% within 10 minutes when the anti-epidemic measures were in place. It was also observed that some entrances experienced significant crowding. Three measures were simulated to find effective ways to increase the get-through efficiency and mitigate the crowding – increasing the distance between security and health checks, utilising automatic infrared thermometers, and arranging volunteers or staff to assist with the registration process. The results demonstrated that using automatic infrared thermometers instead of handheld forehead thermometers proved to be effective in improving passenger efficiency and alleviating crowding at entrances and within the station hall.

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Section: Software Selectionmentioning

confidence: 99%

Study on the Impact of Health Condition Registration and Temperature Check on Inbound Passenger Flow and Optimisation Measures in a Metro Station during the COVID-19 Pandemic

Yu,

2023

PROMTT

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“…В современных средах имитационного моделирования модель разделена на компонентытиповые объекты, которые помимо диаграммы процесса могут содержать дополнительную логику и правила взаимодействия с другими объектами [14]. Согласно разработанной архитектуре адаптивного планирования позаказного производства [15] из автоматизированной системы управления предприятием (АСУП) в имитационный модуль поступают данные о технологических операциях, необходимых для изготовления изделия.…”

Section: имитационная модельunclassified

Multi-Agent Model of Multi-Nomenclature Small Batch Production

Russkikh¹,

Kapulin²

2021

CTAC&R

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Production planning is a key aspect when optimizing production activities. Simulation is one of the most effective methods available for assessing production problems. The principles of adaptive planning consist of making day-to-day operational decisions at the shop floor, predicting equipment availability, assessing performance, and eliminating bottlenecks. Existing research to eliminate bottlenecks has focused on analyzing data from the physical shop, or vice versa, only on the use of simulated data. Convergence between real and simulated data allows, on the one hand, to obtain more information to predict the availability of each workplace, on the other hand, it allows performance assessment for replanning using a simulation model. Aim. Development of optimization tools for production planning using simulation approaches. Materials and methods. This article presents a multi-agent simulation model for each workplace in the workshop, examines the workload of the workshop, and evaluates the productivity of workplaces. Optimization is proposed for optimal utilization of production facilities. As an example illustrating the efficiency and advantage of the proposed model, we took the production process of electronic equipment in the assembly shop. Results. A planning problem and an approach to optimization are formulated. A multi-agent model of multinomenclature small-scale production has been developed. The model provides for the integration of simulation tools with operational planning systems at the data level. Conclusion. The model proposed in the study allows small-scale production to plan the number of jobs and identify bottlenecks in production. The use of a combination of simulation and planning tools ensures enterprise resource management, taking into account dynamic changes in the system.

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“…It is the modeling and analysis of a complex system, one of which is a service system carried out in a computer network. Queuing theory is very much researched because with the queuing model that is carried out, we will know about the input, process and output of the simulation carried out [7]. The best model in conducting analysis related to congestion in a transportation process is using queuing theory.…”

Section: Introductionmentioning

confidence: 99%

Simulation and Modelling Queue of The Ship Betel Stacking Using The Anylogic: Case Study at Port of PT Pelabuhan Indonesia (Pelindo) Sunda Kelapa Region 2

Verawati

Hadi

Hidayatullah

et al. 2022

J. Phys.: Conf. Ser.

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In the midst of the development of the industrial era 4.0 to 5.0, technology plays an important role in various sectors, one of which is transportation. This concept uses science-based Internet of Things, Artificial Intelligence and Robots. The use of applications and other software is the main method for humans to carry out their daily lives, including in the transportation industry, one of which is the Port. The purpose of this paper is to create a ship queue simulation model with a betel stacking system at PT Pelabuhan Sunda Kelapa Region 2. The methodology used for modeling this queue simulation is Anylogic by conducting simulation experiments. simulation model line, the Company can determine the ship queue decision by using betel stacking. The existence of this anylogic system is expected to be able to solve various problems, create many innovations and be able to improve the quality of human resources in various activities, especially in the transportation industry sector which continues to transform until now.

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Simulation and optimization of the cargo terminal in the AnyLogic environment

Cited by 4 publications

References 18 publications

Study on the Impact of Health Condition Registration and Temperature Check on Inbound Passenger Flow and Optimisation Measures in a Metro Station during the COVID-19 Pandemic

Study on the Impact of Health Condition Registration and Temperature Check on Inbound Passenger Flow and Optimisation Measures in a Metro Station during the COVID-19 Pandemic

Multi-Agent Model of Multi-Nomenclature Small Batch Production

Simulation and Modelling Queue of The Ship Betel Stacking Using The Anylogic: Case Study at Port of PT Pelabuhan Indonesia (Pelindo) Sunda Kelapa Region 2

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