AnyLogic
AnyLogic is a multi-method simulation modeling tool developed by XJ Technologies.
History of AnyLogic
In the beginning of 1990s there was a big interest in the mathematical approach to modeling and simulation of parallel processes. This approach may be applied to the analysis of correctness of parallel and distributed programs. The Distributed Computer Network (DCN) research group at Saint Petersburg Technical University developed such a software system for the analysis of program correctness; the new tool was named COVERS (Concurrent Verification and Simulation). This system allowed graphical modeling notation for system structure and behavior. The tool was applied for the research granted by Hewlett Packard (?).
In 1998 the success of this research inspired the DCN laboratory to organize a company with a mission to develop a new age simulation software. The emphasis in the development was placed on applied methods: simulation, performance analysis, behavior of stochastic systems, optimization and visualization. New software released in 2000 was based on the latest advantages of information technologies: an object-oriented approach, elements of the UML standard, the use of Java, a modern GUI, etc.
The tool was named AnyLogic, because it supported all three well-known modeling approaches:
+ Any combination of these approaches within a single model[3]. The first version of AnyLogic was AnyLogic 4, because the numbering continues the numbering of COVERS 3.0.
A big step was taken in 2003, when AnyLogic 5 was released. It was focused on business simulation in the following domains:
- Market and Competition[4],
- Healthcare[5],
- Manufacturing[6],
- Supply Chain[7][8][9],
- Logistics[10],
- Retail[11][12],
- Business Processes[13],
- Social and Ecosystem Dynamics,
- Defense ,
- Project and Asset Management,
- IT Infrastructure,
- Pedestrian Dynamics and Traffic simulation[14],
- Aerospace[15].
- Photovoltaics [16]
The latest major version, AnyLogic 6, was released in 2007. The platform for AnyLogic 6 model development environment is Eclipse. AnyLogic 6 is a cross-platform simulation software as far as it works on Windows, Mac OS and Linux.[17]
AnyLogic and Java
AnyLogic includes a graphical modeling language and also allows the user to extend simulation models with Java code. The Java nature of AnyLogic lends itself to custom model extensions via Java coding as well as the creation of Java applets which can be opened with any standard browser. These applets make AnyLogic models very easy to share or place on websites. In addition to Java applets the Professional version allows for the creation of Java runtime applications which can be distributed to users. These pure Java applications can be a base for decision support tools[18][19].
Multi-method simulation modeling
AnyLogic models can be based on any of the main simulation modeling paradigms: discrete event or process-centric (DE), systems dynamics (SD), and agent-based (AB).
System dynamics and discrete event are traditional simulation approaches, agent based is new. Technically, the system dynamics approach deals mostly with continuous processes whereas "discrete event" (by which we mean all descendants of GPSS also known as process-centric simulation approach) and agent based models work mostly in discrete time, i.e. jump from one event to another.
System dynamics and discrete event simulation historically have been taught at universities to very different groups of students, namely management and economy, industrial and operation research engineers. As a result, there are two distinct practitioners' communities that never talk to each other.
Agent based modeling until recently has been mostly a purely academic topic. However, the increasing demand for global business optimization caused leading modelers looking at combined approaches to gain a deeper insight into complex interdependent processes having very different natures.
How modeling approaches correspond to the abstraction levels. System dynamics dealing with aggregates is obviously used at the highest abstraction level. Discrete event modeling is used at low to middle abstraction. As for agent based modeling, this technology is used across all abstraction levels, and agent may model objects of very diverse nature and scale: at the "physical" level agents may be e.g. pedestrians or cars or robots, at the middle level – customers, at the highest level – competing companies[20].
AnyLogic allows the modeler to combine these simulation approaches within the same model. There is no fixed hierarchy. So, as an example, one could create a model of the package shipping industry where carriers are modeled as agents acting/reacting independently whereas the inner workings of their transport and infrastructure networks could be modeled with discrete event simulation. Similarly, one can model consumers as agents whose aggregate behavior feed a systems dynamics model capturing flows such as revenues or costs which do not need to be tied to individual agents. This mixed language approach is directly applicable to a wide variety of complex modeling problems that may be modeled via any one approach albeit with compromises.
Simulation language
The AnyLogic simulation language consists of following items[21]:
- Stock & Flow Diagrams are used for System Dynamics modeling.
- Statecharts are used mostly in Agent Based modeling to define agent behavior. They are also often used in Discrete Event modeling, e.g. to simulate machine failure.
- Action charts are used to define algorithms. They may be used in Discrete Event modeling, e.g. for call routing, or in Agent Based modeling, e.g. for agent decision logic.
- Process flowcharts are the basic construction used to define process in Discrete Event modeling. Looking at this flowchart you may see why Discrete Event style is often called Process Centric.
The language also includes: low level modeling constructions (variables, equations, parameters, events etc.), presentation shapes (lines, polylines, ovals etc.), analysis facilities (datasets, histograms, plots), connectivity tools, standard images, and experiments frameworks.
AnyLogic libraries
AnyLogic includes the following standard libraries[21]:
- The Enterprise Library is designed to support DE simulation in Manufacturing, Supply Chain, Logistics and Healthcare areas. Using the Enterprise Library objects you can model real-world systems in terms of entities (transactions, customers, products, parts, vehicles, etc.), processes (sequences of operations typically involving queues, delays, resource utilization), and resources. The processes are specified in the form of flowcharts.
- The Pedestrian Library is dedicated to simulate pedestrian flows in a "physical" environment. It allows you to create models of pedestrian-intensive buildings (like subway stations, security checks etc.) or streets (large numbers of pedestrians). Models support statistics collection on pedestrian density in different areas. This ensures acceptable performance of service points with a hypothetical load, estimates lengths of stay in specific areas, and detects potential problems with interior geometry – such as the effect of adding too many obstacles - and other applications. In models created with the Pedestrian Library pedestrians move in continuous space, reacting to different kinds of obstacles (walls, different kinds of areas) as well as other pedestrians. Pedestrians are simulated as interacting agents with complex behavior, but the AnyLogic Pedestrian Library provides a higher-level interface for fast creation of pedestrian models in the style of flowcharts.
- The Rail Library supports modeling, simulating and visualizing operations of a rail yard of any complexity and scale. The rail yard models can be combined with discrete event or agent based models related to: loading and unloading, resource allocation, maintenance, business processes, and other transportation activities.
Beside of these standard libraries user can create his own libraries and distribute them.
See also
References
- ^ The release news on the official web-site.
- ^ Cynthia Nikolai, Gregory Madey. Tools of the Trade: A Survey of Various Agent Based Modeling Platforms, Journal of Artificial Societies and Social Simulation vol. 12, no. 2 2, 31 March 2009
- ^ Andrei Borshchev, Alexei Filippov. From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools,The 22nd International Conference of the System Dynamics Society, July 25–29, 2004, Oxford, England
- ^ Maxim Garifullin, Andrei Borshchev, Timofei Popkov. "Using AnyLogic and Agent Based Approach to Model Consumer Market", EUROSIM 2007, September 2007.
- ^ Kirk Solo, Mark Paich A Modern Simulation Approach for Pharmaceutical Portfolio Management, SimNexus LLC
- ^ Yuri G. Karpov, Rostislav I. Ivanovski, Nikolai I. Voropai, Dmitri B. Popov. Hierarchical Modeling of Electric Power System Expansion by AnyLogic Simulation Software, 2005 IEEE St. Petersburg PowerTech, June 27–30, 2005, St. Petersburg, Russia
- ^ Michael Gyimesi, Johannes Kropf. "C14 Supply Chain Management - AnyLogic 4.0", Simulation News Europe, December 2002.
- ^ Ivanov D.A., Sokolov B., Kaeschel J. "A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations", European Journal of Operational Research, 2009.
- ^ Ivanov D.A. "Supply chain multi-structural (re)-design.", International Journal of Integrated Supply Management, No. 5(1), 19-37., 2009.
- ^ Ilmarts Dukulis, Gints Birzietis, Daina Kanaska. Optimization models for biofuel logistic system, Engineering for Rural Developments, Jelvaga, 29–30 May 2008
- ^ Peer-Olaf Siebers, Uwe Aickelin, Helen Celia, Chris W. Clegg. "understanding Retail Productivity by Simulating Management Practices", EUROSIM 2007, September 2007.
- ^ Peer-Olaf Siebers, Uwe Aickelin, Helen Celia, Chris W. Clegg. "A Multi-Agent Simulation of Retail Management Practices", Proceedings of the Summer Computer Simulation Conference (SCSC 2007), 2007.
- ^ 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", Proceedings of the 2007 Winter Simulation Conference, 2007, Washington, D.C., USA
- ^ V.L. Makarov, V.A. Zitkov, A.R. Bakhtizin. "An agent-based model of Moskow traffic jams", Agent Based Spatial Simulation Workshop, 24–25 November 2008, Paris, France
- ^ David Buxton, Richard Farr, Bart Maccarthy. "The Aero-engine Value Chain Under Future Business Environments: Using Agent-based Simulation to Understand Dynamic Behaviour", MITIP2006, 11–12 September, Budapest.
- ^ Roland Sturm, Hartmut Gross, Jörg Talaga. Material Flow Simulation of TF Production Lines –Results & Benefits (Example based on CIGS Turnkey), Photon equipment conference, March 2009, Munich.
- ^ The full system requirements list on the official web-site.
- ^ Christian Wartha, Momtchil Peev, Andrei Borshchev, Alexei Filippov. Decision Support Tool Supply Chain, Proceedings of the 2002 Winter Simulation Conference, 2002
- ^ Explore different probability distributions and fit your own dataset online - interactive tool
- ^ Yuri G. Karpov. "AnyLogic – a New Generation Professional Simulation Tool", VI International Congress on Mathematical Modeling, September 20-26th, 2004, NizniNovgorog, Russia
- ^ a b AnyLogic on-line help on official vendor web-site
Further reading
- Law, Averill M. (2006). Simulation Modeling and Analysis with Expertfit Software. McGraw-Hill Science. ISBN 978-0-07-329441-4.
- Banks, Jerry; John Carson, Barry Nelson, David Nicol (2004). Discrete-event system simulation - 4th edition. Prentice Hall. ISBN 978-0-13-144679-3.
- Sterman, John D. (2000). Business Dynamics: Systems thinking and modeling for a complex world. McGraw Hill. ISBN 0-07-231135-5.
External links