AnyLogic

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AnyLogic
Basic data

developer The AnyLogic Company
Publishing year 2000
Current  version AnyLogic 8.5.2
Execution environment platform independent
programming language Java SE
category Simulation software
License Commercially
www.anylogic.de

AnyLogic is a multi-method simulation tool developed by The AnyLogic Company (formerly XJ Technologies). It supports system dynamic, event-oriented and agent-based simulation methodologies. The AnyLogic PLE-Edition (Personal Learning Edition) can be used free of charge for educational purposes and for self-study.

history

In the early 1990s there was great interest in a mathematical approach to the modeling and simulation of parallel processes. This approach could be used to analyze the accuracy of parallel and distributed programs. The "Distributed Computer Network" (DCN) research group at the St. Petersburg University of Technology developed a software system to analyze the accuracy of the programs; the new tool was called COVERS (Concurrent Verification and Simulation). This system enabled a graphic model representation for system structure and behavior. The tool was developed in research for Hewlett Packard.

In 1998, stimulated by the success of this research, the DCN research institute founded a company with the aim of developing modern simulation software. The methods used were emphasized during development: simulation, performance analysis, behavioral and stochastic systems, organization and visualization. The new software released in 2000 was based on current developments in information technology: object-oriented approach, elements of the standard UML, modern Java programming language and graphical user interface.

Three simulation approaches by the company

The tool was named AnyLogic because it supports all three known modeling approaches:

Any combination of these approaches is possible within a single model. The first version of AnyLogic is AnyLogic 4, as the numbering of COVERS 3.0 was continued. AnyLogic 5 was released in 2003. The focus was set on business simulation in the following application areas:

The current version, AnyLogic 7, was released in 2014. As the largest release in the past seven years, it contained several major updates to simplify modeling, as well as expanded support for multi-method modeling, reduced coding requirements, and updated libraries. AnyLogic 7.1, also released in 2014, included GIS implementation in the software: in addition to shapefile-based maps, AnyLogic also supports tile-based maps from free online services such as OpenStreetMap .

In 2015, AnyLogic 7.2 came out. with an integrated database and a new Fluid Library. The free Personal Learning Edition (PLE) was also presented in 2015. With AnyLogic 7.3, the first Road Traffic Library appeared in AnyLogic in 2016.

The platform for the AnyLogic 7 model development environment is Eclipse . AnyLogic 7 is a cross-platform simulation software . It can be operated on Windows , Mac OS and Linux .

AnyLogic and Java

AnyLogic includes a graphic modeling language and also enables the user to extend simulation models with Java code. AnyLogic's Java character is suitable both for individual model extensions via Java coding and for designing Java applets that can be opened in any conventional browser. These applets make AnyLogic models easy to send and load onto websites. In addition to the Java applets, the professional version enables the design and distribution of Java runtime applications to users. This exclusive Java application can serve as the basis for decision support tools.

Multi-method simulation modeling

How do simulation approaches correspond to the abstraction level

AnyLogic models can be based on any of the major simulation modeling paradigms : event-oriented or process-centered (DE), system dynamic (SD), and agent-based (AB).

The system dynamic and the event-oriented are traditional simulation approaches; the agent-based approach is a modern method. From a technical point of view, the system dynamic approach deals mainly with continuous processes, the "event-discrete" (this means all descendants of GPSS , also known as the process-centered simulation approach) and the agent-based models, on the other hand, mostly work time-discrete, i.e. H. they switch from one event to another.

System-dynamic and event-oriented simulation has been taught historically at universities with various student groups, including a. Management , economic and operations research engineers. Thus there are two different professional communities that do not communicate with each other.

Until recently, agent-based modeling was almost exclusively an academic subject. Yet the growing demand for global business optimization caused leading modelers to consider combining approaches, giving them better insight into the complex, diverse, interdependent processes.

The modeling approaches are used at different levels of abstraction. The system dynamics that deal with aggregates are applied at the highest level of abstraction. Event-oriented modeling is used with low to medium abstraction. Agent-based modeling can be used on all abstraction levels. In addition, an agent can model objects of various types and sizes: on a “physical” level, agents can e.g. B. as pedestrians, vehicles, robots, at the middle level - as customers, at the highest level - as competitors.

AnyLogic enables the modeler to link these simulation approaches within the same model. There is no fixed hierarchy. Thus, for example, one could design a model for shipping packaging in industry, with the load carriers being modeled as agents that act / react individually, while the internal activities of their transport and infrastructure networks are modeled by event-oriented simulation. Consumers can also be modeled as agents, whose entire behavior is supplied by a system-dynamic model, by recording processes such as income and expenses that do not have to be tied to individual agents. This linguistically mixed approach is directly applicable to a variety of complex modeling problems that can be modeled by any one approach, albeit with tradeoffs.

Simulation language

Simulation language constructions provided by AnyLogic

The AnyLogic simulation language consists of the following elements:

  • Warehouses & flow charts are used for system dynamic modeling.
  • State diagrams are mainly used in agent-based modeling to determine agent behavior. They are also used in event-oriented modeling, e.g. B. to simulate machine failures.
  • Function diagrams are used to determine algorithms. They can be used in event-based modeling, e.g. B. for call distribution, or in agent-based modeling z. B. in the decision logic of the agents.
  • Process flow diagrams represent the basic construction in determining the processes in event-oriented modeling. Looking at this flowchart, it becomes clear why the event-oriented method is often mentioned as process-centered.

The language includes: low-level modeling constructions (variables, equations, parameters, events, etc.), design forms (lines, contours, ellipses), analysis options (data sets, histograms, recording points), connection tools, standard images and experimental frameworks.

AnyLogic libraries

AnyLogic includes the following standard libraries:

  • The Process Modeling Library is designed to support DE simulation in areas such as production, supply chains, logistics and healthcare. Using the Process Modeling Library objects, you can model real systems in terms of data records (transactions, customers, products, components, vehicles, etc.), processes (sequences of operations that normally include series, delays, resource utilization) and resources. The processes are specified in the form of flow charts.
  • The Pedestrian Library is suitable for simulating pedestrian flows in a “physical” environment. It enables the design of building models with intensive pedestrian traffic (such as subway stations, security checkpoints, etc.) or street models (large number of pedestrians). The models support statistical data collection on the number of pedestrians in different zones. This ensures reasonable performance of the services with a hypothetical load, estimates the dwell times in specific zones and detects any problems related to internal geometry - such as the effects of too many obstacles - and other applications. In the models designed with the Pedestrian Library, passers-by move in a continuous space, reacting to various obstacles (walls, different surfaces) and other passers-by. Passers-by are simulated as interacting agents with complex behaviors, but the AnyLogic Pedestrian Library offers a higher-level interface for quickly designing passer-by models in the form of flowcharts.
  • The Rail Library supports modeling, simulation, and visualization of processes within a train station of any complexity or size. The station models can be linked to discrete-event or agent-based models with regard to: loading and unloading, resource distribution, maintenance, business processes and other transport activities.
  • The Fluid Library enables the user to simulate the storage and transfer of liquids, bulk solids or large quantities of general cargo if these are not to be modeled as separate objects. The library contains building blocks such as tank, pipeline, valve, as well as objects for steering, confluence and division of flows. The use of the linear programming solver in the library enables high execution speeds of the models. With the library, AnyLogic can be used efficiently in production as well as in the oil & gas industry and in mining. The user can simulate oil lines and tanks, ore and coal conveyors, as well as production processes that include liquids or bulk materials, such as B. in concrete production.
  • The Road Traffic Library allows the simulation of vehicle traffic on roads. The library supports the detailed modeling of vehicle movement in road traffic. Each vehicle represents an agent who can have its behavioral pattern. The library allows the user to simulate vehicle movement on roads taking into account traffic rules, taking into account traffic lights, zebra crossings and right of way at intersections, parking lots and vehicle movement of public transport. The road traffic library is suitable for the simulation of highway traffic, road traffic, internal transport at production sites or any other system with vehicles, roads and paths. A special traffic density tool allows you to analyze the road network load.

In addition to these standard libraries, the user can design and share their own libraries.

Model animation

AnyLogic supports interactive 2D and 3D animations.

The software enables users to import CAD drawings as DXF files and then visualize models on them. This function can be used to animate processes within objects such as factories, warehouses, hospitals and the like. It is mainly used in event-based modeling, in manufacturing, healthcare, engineering, and construction. AnyLogic also enables 3D animation and contains a collection of ready-to-use 3D objects on topics such as buildings, roads, rails, shipping, transport, energy, warehouses, hospitals, equipment, airports, supermarkets or cranes.

Models can contain custom user interfaces that users can use to configure experiments and change input data.

Geodata models, GIS integration

AnyLogic models can use maps as layouts, which is particularly useful in supply chain, logistics and transport simulation. AnyLogic supports the traditional, shapefile-based card standard SHP from ESRI . In addition, tile-based maps can also be used by free online services, such as B. OpenStreetMap . Tile-based maps allow the modeler to use map data in models and to automatically create geodata routes for agents. The main functions of tile-based maps in AnyLogic are:

  • The model has access to all data stored together with the online map, such as cities, regions, road networks and objects (hospitals, schools, bus stops, etc.).
  • Agents can be placed at specified points on the map and moved along existing roads or routes.
  • Users can create required elements within the model using the search function.

Model integration with other IT infrastructure

AnyLogic models can be exported as Java applications and thus run independently or integrated into other software. Optionally, an exported AnyLogic model can be built into other software and used as an additional module in ERP, MRP and TMS systems.

Another typical use is the integration of AnyLogic models with TXT, MS Excel or MS Access files and databases (MS SQL, My SQL, Oracle etc.). In addition, AnyLogic models contain their own database based on HSQLDB.

Free educational version

The AnyLogic Personal Learning Edition (PLE) has been available free of charge for the purpose of further training and self-study since 2015. The PLE license is not limited in time, but the size of the models that can be created is limited.

For public research at educational institutions, users can purchase discounted University Researcher licenses that allow unlimited model sizes and contain many of the functionalities of AnyLogic Professional Licenses.

anyLogistix supply chain optimization software

AnyLogic does not contain its own library for supply chain simulation. The AnyLogic Company has instead developed a separate software tool for this area - anyLogistix. This spin-off product was presented as AnyLogic Logistics Network Manager in 2014 and renamed anyLogistix in 2015.

anyLogistix is ​​based on the AnyLogic engine, GIS, and a GUI specially designed for this application. It also contains algorithms and techniques specifically for the design and optimization of supply chains. anyLogistix is ​​fully integrated with AnyLogic. For example, AnyLogic can be used to customize objects within anyLogistix, including warehouses, manufacturing facilities, suppliers, inventory, sourcing and transportation strategies.

See also

literature

  • Averill M. Law: Simulation Modeling and Analysis with Expertfit Software . McGraw-Hill Science, 2006, ISBN 978-0-07-329441-4 .
  • Jerry Banks, John Carson, Barry Nelson, David Nicol: Discrete-event system simulation - 4th edition . Prentice Hall, 2004, ISBN 978-0-13-144679-3 .
  • John D. Sterman: Business Dynamics: Systems thinking and modeling for a complex world . McGraw Hill, 2000, ISBN 0-07-231135-5 .

Web links

Wikibooks: Simulation with AnyLogic  - Learning and teaching materials (English)

Individual evidence

  1. ↑ AnyLogic changelog. Retrieved April 23, 2020 .
  2. ↑ Software documentation on the AnyLogic company website.
  3. ↑ a b c Edition comparison on the AnyLogic company website.
  4. ↑ Cynthia Nikolai, Gregory Madey. Tools of the Trade: A Survey of Various Agent Based Modeling Platforms (PDF; 298 kB), Journal of Artificial Societies and Social Simulation vol. 12, no.2 2 , 31 March 2009.
  5. ↑ Andrei Borshchev, Alexei Filippov. From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools (PDF; 518 kB), The 22nd International Conference of the System Dynamics Society , July 25-29, 2004, Oxford, England
  6. ↑ Maxim Garifullin, Andrei Borshchev, Timofei Popkov. "Using AnyLogic and Agent Based Approach to Model Consumer Market" , EUROSIM 2007 , September , 2007 .
  7. ↑ Kirk Solo, Mark Paich A Modern Simulation Approach for Pharmaceutical Portfolio Management ( Memento of the original from July 16, 2011 in the Internet Archive ) Info: The archive link has been inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. (PDF; 439 kB), SimNexus LLC @1@ 2Template: Webachiv / IABot / www.simnexus.com
  8. ^ Yuri G. Karpov, Rostislav I. Ivanovski, Nikolai I. Voropai, Dmitri B. Popov. Hierarchical Modeling of Electric Power System Expansion by AnyLogic Simulation Software ( Memento from February 22, 2012 in the Internet Archive ), 2005 IEEE St. Petersburg PowerTech , June 27-30, 2005, St. Petersburg, Russia
  9. ↑ Michael Gyimesi, Johannes Kropf: C14 Supply Chain Management - AnyLogic 4.0 . ( Memento of the original from July 25, 2011 in the Internet Archive ; PDF; 113 kB) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. In: Simulation News Europe. December 2002. @1@ 2Template: Webachiv / IABot / www.argesim.org
  10. ^ DA Ivanov, B. Sokolov, J. Kaeschel: A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations . ( Memento of the original from August 12, 2011 in the Internet Archive ; PDF; 932 kB) Info: The archive link was automatically inserted and not yet checked. Please check the original and archive link according to the instructions and then remove this notice. In: European Journal of Operational Research. 2009. @1@ 2Template: Webachiv / IABot / www.tu-chemnitz.de
  11. ^ DA Ivanov: Supply chain multi-structural (re) -design . ( Memento of the original from August 12, 2011 in the Internet Archive ; PDF; 489 kB) Info: The archive link was automatically inserted and not yet checked. Please check the original and archive link according to the instructions and then remove this notice. In: International Journal of Integrated Supply Management. No. 5 (1), 2009, pp. 19-37. @1@ 2Template: Webachiv / IABot / www.tu-chemnitz.de
  12. ↑ Ilmarts Dukulis, Gints Birzietis, Daina Kanaska. Optimization models for biofuel logistic system (PDF; 170 kB), Engineering for Rural Developments , Jelvaga, 29-30 May 2008.
  13. ↑ Peer-Olaf Siebers, Uwe Aickelin, Helen Celia, Chris W. Clegg: “Understanding Retail Productivity by Simulating Management Practices” (PDF; 502 kB) EUROSIM 2007 , September , 2007.
  14. ↑ Peer-Olaf Siebers, Uwe Aickelin, Helen Celia, Chris W. Clegg. A Multi-Agent Simulation of Retail Management Practices ( Memento of the original from December 28, 2009 in the Internet Archive ) Info: The archive link was automatically inserted and not yet checked. Please check the original and archive link according to the instructions and then remove this notice. (PDF; 493 kB), Proceedings of the Summer Computer Simulation Conference (SCSC 2007) , 2007. @1@ 2Template: Webachiv / IABot / ima.ac.uk
  15. ^ Arnold Greenland, David Connors, John L. Guyton, Erica Layne Morrison, Michael Sebastiani. "IRS post-filing processes simulation modeling: a comparison of DES with econometric microsimulation in tax administration" (PDF; 368 kB), Proceedings of the 2007 Winter Simulation Conference , 2007, Washington DC, USA
  16. ↑ VL Makarov, VA Zitkov, AR Bakhtizin. An agent-based model of Moskow traffic jams . ( Memento of the original from April 16, 2011 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. , Agent Based Spatial Simulation Workshop , 24.-25. November 2008, Paris, France @1@ 2Template: Webachiv / IABot / s4.csregistry.org
  17. ↑ David Buxton, Richard Farr, Bart Maccarthy. "The Aero-engine Value Chain Under Future Business Environments: Using Agent-based Simulation to Understand Dynamic Behavior" , MITIP2006 , September 11-12, Budapest.
  18. ↑ Roland Sturm, Enrico Quasdorf "Equipment Library - Factory simulation using the example of photovoltaic factories " ( Memento of the original from October 13, 2012 in the Internet Archive ) Info: The archive link was inserted automatically and not yet checked. Please check the original and archive link according to the instructions and then remove this notice. (PDF; 2.9 MB) @1@ 2Template: Webachiv / IABot / www.software-saxony.de
  19. ↑ Blog entry ( Memento of the original from August 1, 2016 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. on the AnyLogic company website. @1@ 2Template: Webachiv / IABot / www.anylogic.com
  20. ↑ Overview of new features on the company website .
  21. ↑ Software documentation.
  22. ↑ Blog entry ( Memento of the original from June 24, 2016 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. on the AnyLogic company website. @1@ 2Template: Webachiv / IABot / www.anylogic.com
  23. ↑ Blog entry ( Memento of the original from June 24, 2016 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. on the AnyLogic company website. @1@ 2Template: Webachiv / IABot / www.anylogic.com
  24. ↑ Blog entry ( Memento of the original from June 24, 2016 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. on the AnyLogic company website. @1@ 2Template: Webachiv / IABot / www.anylogic.com
  25. ↑ The complete list of system requirements on the AnyLogic website .
  26. ↑ Christian Wartha, Momtchil Peev, Andrei Borshchev, Alexei Filippov. Decision Support Tool Supply Chain ( Memento from June 1, 2006 in the Internet Archive ), Proceedings of the 2002 Winter Simulation Conference , 2002.
  27. ↑ Explore different probability distributions and fit your own dataset online - interactive tool
  28. ^ Yuri G. Karpov: AnyLogic - a New Generation Professional Simulation Tool . (PDF; 254 kB) VI International Congress on Mathematical Modeling , September 20-26th, 2004, NizniNovgorog, Russia
  29. ↑ a b AnyLogic online help on the official website
  30. ↑ Editions Comparison - AnyLogic Simulation Software. Retrieved June 2, 2016 .
  31. ↑ AnyLogic 7 Simulation Software: New Features Overview. Retrieved June 2, 2016 .
  32. ↑ AnyLogic Professional - AnyLogic Simulation Software. Retrieved June 2, 2016 .
  33. ^ AnyLogic Changes History. Accessed January 21, 2020 .
  34. ↑ Supply Chain Optimization and Simulation Software - anyLogistix. www.anylogistix.com, accessed June 2, 2016 .