AnyLogic Software Research Articles

Применение имитационного моделирования в процессах постройки судна

This article provides an example of the application of the method of simulation modeling of ship construction processes in AnyLogic software. The process is briefly described and the logistics of building a barge produced at shipyards is characterized, and a map of the production process is prepared. In conclusion, three possible modernization options were proposed, which consist in technological, organizational improvements and a variant combining both of these solutions. AnyLogic software was used for a comparative analysis of the proposed options in relation to the process in the basic version. This method allows you to obtain accurate data for making informed decisions without the need for physical tests. The use of simulation modeling is a key tool for optimizing shipbuilding processes and further development of the industry.

Estimation of Domestic Load Profile for Effective Demand-Side Management

In this article domestic base and shift based load profile are estimated for effective Demand Side Management (DSM). Domestic electricity consumption in Pakistan accounts for approximately 40% of total electricity sales. Effective DSM can reduce electricity consumption. Power generation companies are increasingly recognising the importance of analysing their customers' consumption patterns. This article proposes an agent-based modelling approach for forecasting household electricity consumption profile. AnyLogic software is used for establishing the model that uses variables and functions to estimate base and shiftable load of three hundred households. This article also estimates the weekly and 24- hour load profile for effective DSM operations by smart grid infrastructure. The results show that the agent-based simulation closely approximates real-time data, with a difference of only 2.4%.

Simulation Modeling of the Operation of the Toll Plaza with Reversible Lanes

The construction of toll roads depends on the available territory. The limited area often does not allow the construction of a full-fledged toll plaza (hereinafter referred to as TP) with high capacity and many lanes. In such cases, the configuration of TP is linked with the configuration of reversible lanes. Reversible lanes carry traffic and help optimize traffic flow. The challenge is to choose the optimal configuration of a TP that provides the highest capacity (traffic flow increases in both directions) and helps control operators’ errors resulting in traffic congestion problems. The present study estimates TP with reversible lanes throughput capacity in different configurations and traffic flow parameters. The study employs discrete-event simulation modeling in the AnyLogic software environment. Our results show the optimal configuration of the reversible lanes and explain what traffic flow parameters affect their capacity. The paper concludes with practical recommendations on how to effectively apply simulation modeling to a TP operation and optimize it.

Study on the propagation characteristics of shockwave in dense crowd in corner passage

Crowd shockwaves are prone to occur when evacuating dense crowds, especially in areas with corner passages, leading to congestion and accidents. The characteristics of shockwaves in corner passages need further exploration. This study used AnyLogic software based on the social force model to construct scenarios. The propagation mechanism of crowd shockwaves was revealed through simulation analysis of the changes in wave amplitude, duration, and propagation velocity of crowd density waves under different corner angles (0–90°). It was found that a 45° corner passage has advantages compared to other corner passages for evacuation. At higher desired velocities, pedestrians form a bottleneck-like area at the corner of the passage, resulting in crowd shockwaves. Because of social forces, congestion occurs primarily in the corner area. To alleviate this pressure, pedestrians actively adjust the distance between themselves and others. The time interval between the two shockwaves decreases as the desired velocity increases. The propagation time of crowd shockwaves before the corner is generally more significant than the duration after the corner. This study could guide the elimination or reduction of crowd shockwaves, improving pedestrians' evacuation efficiency and safety in evacuation passages.

Trade-offs between stump-to-roadside lead time and harvesting cost, when using different number of operators in a harvester-forwarder system

AbstractFor customer-oriented wood supply, buffering is required for flexibility to handle interactions in the wood procurement system. This includes balancing lead-time and operational cost by using stocks and production capacity as buffers. Despite the well-known challenge to balance the interactions between harvesting and forwarding in Nordic mechaniced CTL-operations, there has been limited research on how the machine groups can be staffed to enable flexibility and more focus on other measures to create flexibility. Therefore, this study explored trade-offs between wood lead-time and harvesting cost in the stump-to-roadside part of the wood supply chain by altering the numer of full-time working operators in the harvesting groups. This was done using discrete-event simulations implemented in Anylogic software. Input data included information about operational conditions in 1500 forest stands. The results revealed that the best balance was to have sufficient harvesting capacity to adjust wood lead times at the expense of increased harvesting costs. Of the tested options, the best balance was achieved when staffing a two-machine group with three operators, and thereby allocating 50% of the used work-shifts to regulating the field wood stock between the two machines. This resulted in the shortest lead times and the smallest harvesting cost increase. Compared to the option with no flexibility for stock adjustment (4 operators), the average lead-time could be reduced to one tenth at a cost increase of 3.4%. These findings have the potential to improve decisions of how harvesting groups are staffed to balance specific objectives of desired lead times and costs, which migh prove to be a valuable addition to the already used measures to manage wood flow.

Использование программы ANYLOGIC для моделирования процессов с использованием контейнеров-трансформеров

This scientific article discusses the possibilities of using Anylogic software to simulate transportation using transformable containers. The main attention is paid to the analysis of the unique characteristics of the transformable container, including its ability to transform, mobile warehouse technology, as well as modification of Anylogic software tools to develop models for improving loading and unloading, transport, transshipment and warehouse operations, based on new technical design solutions containers that increase the efficiency of transport and technological systems. The article analyzes specific functions and data libraries of the Anylogic program, which allow taking into account the unique characteristics of transformable containers when modeling transportation by improving production processes, including loading and unloading, transport, transshipment and warehouse operations. Original algorithms are proposed to optimize loading and unloading, as well as tools for planning routes taking into account the specific use of such containers. Ways to integrate these approaches into existing logistics systems are proposed and the potential benefits of their application to achieve higher efficiency and sustainability of urban transport and technological systems are described.

Research on risk assessment model and simulation of online group polarization in emergencies.

This study proposes a framework for the risk structure of group polarization in the online information of sudden public health incidents, as well as the causes and constraints of group polarization distributed in the ternary space. Then, combining the above two and based on the concept of phase change space, a simulation model of group polarization of online information in sudden public health incidents was constructed by reflecting the risk of group polarization with the number of network users who hold extreme views. The system dynamics simulation of the model is carried out by using the software Anylogic, and predict the evolution trend of the model from the perspective of simulation. The research results indicate that the model built in this study can effectively simulate the formation and dissemination of extreme opinions in the online public opinion of public health emergencies. The vital factors or constraints on the group polarization include emotional guidance, heat reduction, as well as and life pressure.

Multi-agent modeling of traffic organization in urban agglomerations

The authors consider the features of multi-agent modeling for traffic optimization in the central areas of cities. While evaluating the unique challenges associated with the high concentration of vehicles, pedestrians and historical buildings, the potential of multi-agent systems to effectively solve the problem of congestion, safety and quality of life in urban areas is investigated. The potential of multi-agent modeling in the context of traffic management in the central areas of the city allows us to identify the key challenges and opportunities. Many scientists address the main aspects of such modeling and use them in the transport and road sectors. A review of current research and development has shown that multi-agent models aim to simulate and optimize the supervision and control of transportation in various traffic scenarios. Modeling traffic organization in the central areas of cities is one of the main elements of urban development planning and management. Due to the growing population of cities and the increasing number of vehicles, the problems of congestion, air pollution, and inefficient use of infrastructure are becoming increasingly relevant. Therefore, it can be noted that multi-agent traffic modeling opens up new prospects for developing effective traffic management strategies, providing a flexible and adaptive solution to these problems. The research analyzes the existing approaches, identifies the system`s key components, and develops a model that demonstrates the interaction between agents and the environment based on a mathematical description. A practical simulation of the model, carried out using the AnyLogic software on the example of Lesia Ukrainka Boulevard in Kyiv, confirms the effectiveness of the multi-agent approach. The results of the study indicate the possibility of applying the developed model to improve intelligent information systems for traffic flow management, which opens up new prospects for improving traffic in the central areas of cities.

Quantum entanglement and self-attention neural networks: An investigation into passengers and stops characteristics for optimal bus stop localization

Urban transportation significantly contributes to global carbon emissions, thus emphasizing the importance of green and efficient alternatives like public transportation. Enhancing the appeal of public transport through the strategic placement of bus stops can mitigate carbon emissions concurrently. This research proposes a Quantum Entangled Self-Attention Neural Networks (QESANN) model that considers both the passengers and stops characteristics to optimize bus stop locations. The QESANN model integrates the complexity of the relationship between passengers and bus stops characteristics, thereby fostering a more holistic approach to bus stop placement. It uses a Conditional Random Field (CRF) to initialize and process the attributes of both commuters and bus stops through quantum entanglement. The Vehicle Specific Power (VSP) model is employed to gage the variation in bus carbon emissions pre and post bus stop location optimization. Simulation tests, conducted via the Anylogic software and the IBM Quantum platform, demonstrated promising results. Over a yearly travel cycle for 1,000 individuals, the number of bus commuters rose from 322 to 651, concurrently reducing urban traffic carbon emissions by 430,243.70 kg annually. These findings affirm the effectiveness of the proposed QESANN model in enhancing the appeal of bus stops, reducing carbon emissions from urban transportation, and fostering a more sustainable urban environment.

A multi-agent reinforcement learning approach for ART adaptive control in automated container terminals

Intelligent transportation equipment represented by Artificial Intelligence Robot of Transportation (ART) has been gradually applied to automated container terminals (ACT). ARTs have higher intelligence and distributed autonomous decision-making capability compared to AGVs. The production and operation of ACT require strict loading plans based on container types and destination ports, which puts strict requirements on the ART loading task sequence. ART travel time from the yard to the quay is highly uncertain due to special scenarios such as traffic flow convergence and turning in narrow areas, which will lead to long waits for ART due to out-of-sequence arrivals at the quay. Therefore, it is necessary to regulate the speed of ART to adjust the timing of ART arriving at the quay. However, existing scheduling systems tend to ignore the impact of ART speed and loading sequence constraints on terminal operations. To optimize the multi-ART control problem of ACT, the waiting time of ART at the quay is taken as the optimization goal, and the speed regulation of ART during each task is defined as a Markov decision process. Then, by incorporating reinforcement learning and a multi-agent approach, an adaptive decision-making method is developed to generate the optimal speed regulation strategy. This method interacts with the multi-agent simulation environment to obtain real-time status information and learns strategies online to improve the intelligence of individual agents and the collaborative capabilities of the agent group. Finally, a multi-agent simulation model embedded with a reinforcement learning agent is established on AnyLogic software. Simulation results show that this method can effectively reduce the waiting time of ART, improve the coherence and efficiency of loading operations, and exhibit good performance in online scenarios that consider emergency tasks. The results indicate that the speed of ART in ACTs with parallel layout of the yard can impact the operational efficiency of the system. Furthermore, by appropriately defining the reward function and training method, collaborative behaviour among equipment can be enhanced, ultimately optimizing the overall performance of the system.

Analysis and Modeling of Queuing System Simulation in Payment Process at Minimarket (Case Study of Minimarket X Yogyakarta)

The purpose of this study is to analyze the queuing system at Minimarket X so as to minimize the number of queues. The method in this writing uses a discrete event simulation method with the help of Anylogic software. Simulation is used as a method to analyze problems that exist in the payment system at the Minimarket, while Anylogic software as an illustration that can facilitate the queuing system so that it is clearer and easier to understand. Observations conducted for 20 days show that the queuing system applied by Minimarket X is Multi Channel – Single Phase and First Come First Served (FCFS) or First In First Out (FIFO) with 4 cashier officers (M/M/4). Each cashier is tasked with serving customers and processing the products purchased by scanning them and packing each grocery. The average number of Minimarket visitors every day is 22 customers per hour with a queue length of 10 to 11 customers per hour, and the average waiting time for customers to be served is around 27 to 30 minutes. The simulation used through anylogic software obtained error results within 67 minutes 43 seconds.

A system dynamics-based model for the evolution of environmental group events

Based on the system dynamics theory, this paper establishes an environmental mass event evolution model and explores the evolution law of mass events caused by environmental problems. From a methodological point of view, the mixed-strategy evolutionary game principle and dynamic punishment measures are combined, and simulation analysis is carried out by Anylogic software, and the results show that there is no stable evolutionary equilibrium solution for the two sides of the game in the traditional asymmetric mixed-strategy game model, and after adjusting the game payoff matrix and incorporating the dynamic punishment strategy, stable evolutionary equilibrium solutions appear in the evolutionary game model, and the system begins to tend to be stabilized. The process and conclusions of the simulation experiment provide methodological reference and theoretical support for the analysis of the evolution of environmental mass events.

Modeling and evaluating costs and greenhouse gas emissions in solid waste management based on system dynamics in a mega-city: The case of Xi'an

With the escalating generation of municipal solid waste (MSW) and the increasing utilization of collection and transportation (C&T) vehicles within the MSW classification system, the associated costs and greenhouse gas (GHG) emissions from waste drop-off, as well as the C&T processes, have risen sharply. However, the mesoscopic view of the waste drop-off and C&T system is limited. Therefore, we divided the waste classification management (WCM) system into three subsystems: generation and drop-off, C&T, and disposal. Based on system dynamics theory, the logical relationships between relevant parameters in each subsystem were established. A WCM system dynamics model, which focused mainly on the drop-off and C&T processes, was constructed using Anylogic software. Using sensitivity, scenario, and uncertainty analyses, the economic impact and GHG emissions of the WCM system were analyzed in detail. The results showed that the waste drop-off and C&T processes accounted for 54.29–57.87% ($47.31 per ton) and 24.54–26.83% ($21.39–21.93 per ton) of the total cost in the whole waste management chain, respectively. GHG emissions were mainly generated in disposal facilities (116.84–257.86 kg CO2-eq/t), followed by C&T (19.02–20.55 kg CO2-eq/t) and drop-off processes (12.68–18.78 kg CO2-eq/t). The system cost and GHG emissions were significantly influenced by the components of the source-separated waste and operational parameters of the applied C&T vehicles. This study not only provides a basis for WCM policy formulation but also a tool for the design and optimization of waste C&T systems.

Optimization of Emergency Epidemic Prevention Material Reserve and Supply System of Shanxi Province in China: Based on Anylogic Simulation

Due to the randomness and uncertainty of epidemic occurrence, there are insufficient emergency supplies and low efficiency of transportation equipment in Shanxi Province. In order to meet the needs of materials in Shanxi Province, it is urgently necessary to establish a reserve and supply system with perfect facilities and equipment. According to the geographical location of 11 prefecture-level cities in Shanxi Province and the actual situation of transportation equipment, this paper simulates the location of warehouse construction in each city. Through simulation modeling, the emergency epidemic prevention materials reserve and supply system of prefecture-level cities in Shanxi Province was simulated under the epidemic situation. The research idea of "simulation-analysis-optimization-summary" was defined, and the AnyLogic software was used to simulate and analyze the emergency epidemic prevention materials reserve and supply system of the whole Shanxi Province. Through the simulation of different scenarios, the optimization direction of transportation equipment is obtained. Based on the optimization effect of each plan of transportation equipment loading on the emergency epidemic prevention materials reserve and supply system in Shanxi Province, the best optimization plan was obtained. The results show that the efficiency of transportation equipment allocation is improved and the loading capacity of transportation equipment is reasonable and effective. After optimization, the order backlog of each prefecture-level city storage warehouse is reduced, and the order processing time is reduced. The optimization ideas proposed in this paper provide the optimization direction for the emergency epidemic prevention materials reserve and supply system in Shanxi Province, and also have certain guiding significance for how to deal with major public health emergencies.

Exhibition Space Circulation in Museums from the Perspective of Pedestrian Simulation

Contemporary studies largely concentrate on the physical aspects of architecture, yet within the sphere of design, the gap between user experience and the designer’s intention is an undeniable fact. This gap, illustrating the contrast between the spatial perception and the actual physical space, to some degree, mirrors preferences in human spatial behavior. It accentuates the complex relationship between human cognitive functions and spatial layout, underlining the critical role of spatial perception in architectural design and planning. This prompts the question of whether perceptions of internal traffic flow within buildings also suffer from spatial distortions. Focusing on museums, and by examining circulation paths and spatial features, a virtual museum model is devised. The research employs a holistic and reductionist approach (complex systems theory) to forge a link between circulation components and the spatial experience of architecture. Utilizing agent-based modeling tools for simulating pedestrian movements, it investigates how different circulation patterns and spatial relationships influence pedestrian behavior. The study proposes a museum circulation optimization strategy, grounded in quantifying spatial experience through Anylogic software analysis. This strategy is aimed at enhancing the design of internal traffic flows in future museum projects, offering fresh insights into museum design research, and probing into new possibilities for using pedestrian simulation software.

Управление ресурсами пожарных частей с использованием имитационного моделирования

Strategic planning is an important aspect of resourcing security services. The effectiveness of the fire service depends largely on the allocation of limited resources in fire services and the location of fire stations. This paper discusses the application of simulation modelling and AnyLogic software to investigate the functioning of a fire station. The model allows you to evaluate its effectiveness depending on the resource equipment, and evaluate the dynamics of changes in the readiness ratios of fire departments. The use of this model allows solving the problem of resource management and their optimisation.

Passenger Routing Algorithm for COVID-19 Spread Prevention by Minimising Overcrowding

COVID-19 has become a pandemic which has resulted in measures being taken for the health and safety of people. The spreading of this disease is particularly evident in indoor spaces, which tend to get overcrowded with people. One such place is the airport where a plethora of passengers gather in common places, such as coffee shops and duty-free shops as well as toilets and gates. Guiding the passengers to less overcrowded places within the airport may be a solution to reduce disease spread. In this paper, we suggest a passenger routing algorithm whereby the passengers are guided to less crowded places by using a weighting factor, which is minimised to accomplish the desired goal. We modeled a number of shops in an airport using the AnyLogic software and we tested the algorithm showing that the exposure time is less with routing and that people are appropriately spread out across the common spaces, thus preventing overcrowding. Finally, we added a real airport in Kavala, Greece to show the efficiency of our approach.

Research on emergency evacuation behavior rules of pedestrians under fire and explosion accidents in chemical parks considering social relationships

Chemical parks present a high risk of sudden accidents such as fires and explosions, given the significant number of hazardous sources present. This is why emergency evacuation after accidents is so essential. The behavior of crowds during evacuation is complex, and social relationships among pedestrians can have differentiated effects on the evacuation process. However, most of the current crowd evacuation research has focused on life scenarios and natural disaster contexts. Less attention has been paid to the emergency evacuation of crowds affected by social relations in the context of chemical accident disasters. A comprehensive evacuation model that considers the dynamic evolution of crowd transfer both within and outside the factory area is proposed in this paper. Using the Anylogic software based on the social force model, this study constructs emergency evacuation scenarios for crowd in the context of fire and explosion accidents, and toxic gas leakage incidents. Specifically, this study analyzes the impact of three factors, namely inter-personal distance, group size, and proportion of different group sizes in the total population, on the evacuation efficiency. It has been found that when large groups of pedestrians are split into smaller ones for evacuation, the evacuation efficiency can be effectively improved. The study includes calculations of the lethal range of a toxic gas and simulated the process of relocating large crowds of people to nearby shelters. In addition, a strategy for deploying pedestrian groups based on social relationships was developed for the context of mass evacuation. These measures have the potential to optimize the evacuation efficiency of pedestrian groups in chemical parks, including expanding and modifying shelters, diverting dense crowds from residential plots, using interpersonal spacing of 0.1 m, and splitting large groups of pedestrians into smaller ones. The research results can provide a reference for decision making for large-scale group evacuation in chemical parks, and improve the emergency evacuation capability and local risk response capability in chemical parks.

Simulation Modeling of the Process of Accident Risk Realization during Stripping Operations at an Open-Pit Coal Mine

Introduction. The need to increase the level of comprehensive safety, reduce accident and injury rates, minimize the risk of failures, accidents and catastrophes determines the relevance of research on the relationship of elements of the "human–machine–environment" (H–M–E) system during open-pit mining. One of the most effective mechanisms for studying the functional characteristics of the H–M–E system of a coal mine is to conduct simulation modeling in order to identify problematic situations that trigger accidents with catastrophic consequences and injury to personnel. Simulation modeling of a technological process involves constructing a model of a real system and setting up computational experiments to describe the behavior of the system and evaluate various strategies that ensure its functioning. The aim of the research was to adapt simulation modeling technologies to solve the problem of complex safety during open-pit mining. Within the framework of the study, the task was to determine the elements that made the greatest contribution to the implementation of risks in the H–M–E system during stripping operations at a coal mine. The simulated subsystems were "human", "machine", "environment", and "weather conditions". Materials and Methods. Stripping process was considered in the ARIS eEPC (extended Event Driven Process Chain) methodology as a business process linking a set of subprocesses and/or business operations. To build a simulation model in the AnyLogic software environment, the business process of stripping works in ARIS eEPC notation was described by a graph representing a structure consisting of objects and connections between them. This approach allowed us to structure the sequence of events and operations and determine alternative outcomes that arose during stripping operations. Results. As part of the research, a method was developed for translating the formal model of the stripping business process in ARIS eEPC notation into a combined simulation model of AnyLogic. Based on the developed method, a series of machine experiments was carried out. The elements influencing the realization of the risk of accidents in the H–M–E system of a coal mine were determined. Discussion and Conclusion. For the first time in the domestic practice of research of the H–M–E system, simulation modeling technologies have received an application for the analysis of complex safety indicators during open-pit mining. According to the simulation experiment results, it was found that the main influence on the decrease in the reliability of the "machine" subsystem was exerted by the human factor, which, together with the psychophysiological properties of a person, enhanced the development of the domino effect when implementing various types of risks. The presented results and experimental approbation of simulation modeling technology can have advanced use in the analysis of complex technical systems safety, taking into account the influence of human and man-made factors.

Exploring the Impacts of Exit Structures on Evacuation Efficiency

In the context of a fire emergency, safe and efficient exits are of paramount importance for pedestrian evacuation. The recent rapid development in the construction industry has rendered exit structures more diverse and complex. However, little attention has been paid to the influence of exit structures on the efficiency of crowd evacuation processes. In this paper, a tentative experiment was designed to preliminarily reveal the effects of five exit structures (Exit 1, Exit 2, Exit 4, Exit 5, and Exit 3 as examples for comparison) on crowd evacuation. Exit 1 has door leaves opening outward. Exit 2 has door leaves opening inward. Exit 3 has no leaves. Exit 4 consists of double-layer exit doors with the doors opening outward. Exit 5 comprises double-layer exit doors with the doors opening both sides outwards Subsequently, according to the properties of this experiment, a social force-based simulation model was established using the AnyLogic software 8.8.4. By changing the exit width and the crowd density, data such as evacuation time, flow rate, crowd density, and time delay were investigated in detail. The results revealed a notable variation in the evacuation efficiency depending on the deign of the exit. The respective flow rates for Exits 1, 2, 3, 4, and 5 were 0.66 people/(m·s), 0.77 people/(m·s), 0.80 people/(m·s), 0.71 people/(m·s), and 0.66 people/(m·s). Although Exit 3 excelled in terms of evacuation efficiency, it is not directly applicable to real architectural structures. Therefore, Exit 2 emerged as a highly promising solution in terms of flow rate and population control in the exit area, underscoring the effectiveness and practicality of its structural design. It is prospective that the results of this study can offer engineering and technical professionals valuable references and guidance concerning the design of exit structures.