Multi-method modeling

Transcription

1 Multi-method modeling Dr. Andrei Borshchev CEO, The AnyLogic Company UNSW Sydney, February 2013 The AnyLogic Company

2 The three methods in simulation modeling The three modeling methods are the three different viewpoints the modeler can take when mapping the real world system to its image in the world of models High abstraction level [minimum details macro level strategic level] Medium abstraction level [medium details meso level tactical level] Low abstraction level [maximum details Micro level Operational level] Aggregates, global feedback loops, influences, trends Discrete Event (process based) Modeling Agent Based Modeling Individual objects, exact sizes, velocities, distances, timing System Dynamics The AnyLogic Company 7

3 Why multi-method modeling? Sometimes, at the beginning of the project it is not clear which abstraction level and which method should be used The modeler may start with, say, a highly abstract system dynamics model and switch later on to a more detailed discrete event model Frequently, the problem cannot completely conform to one modeling paradigm Different components may be best described by using different methods. Using a traditional single-method tool, the modeler inevitably Either starts using workarounds (unnatural and cumbersome language constructs), or Just leaves part of the problem outside the scope of the model (treats it as exogenous). If we want to capture business, economic, and social systems in their natural complexity and interaction, "thinking single-method" becomes a serious limitation The AnyLogic Company 12

4 Simulation modeling software Traditional tools are designed to support one particular modeling approach System dynamics Discrete event modeling Agent based modeling Dynamic systems VenSim PowerSim ithink Arena ExtendSim Simul8 AutoMod PROMODEL Simio Witness FlexSim [Academic tools:] Swarm RePast NetLogo ASCAPE MASON MATLAB VisSim LabView Easy5 The AnyLogic Company 13

5 The main idea behind AnyLogic Support all three modeling methods on a single modern objectoriented platform Dynamic systems The modeler can choose from a wide range of abstraction levels/methods and can efficiently vary them while working on the model The modeler can combine different methods in one model Agent based modeling Discrete event (process based) modeling System dynamics The AnyLogic Company 14

6 Model architectures Agents SD DE (Process model) Agents + SD environment (e.g., population + city infrastructure) Agents + process model (e.g., clients + service) SD + process model (e.g., demand + production) SD inside agent (e.g. consumer s individual decision making) Process model inside agent (e.g. business process in a company in a bigger supply chain model) Agents become entities (e.g., patients with chronic diseases return to hospital) and so on in any combination The AnyLogic Company 15

7 Example 1: Supply chain and market DE model of a supply chain SD model of new product diffusion implements missing flow The AnyLogic Company 16

8 Example 2: Product portfolio and investment policy add new agents have costs AB model of product portfolio bring revenue SD model of investment policy The AnyLogic Company 17

9 Example 3: Cell phone users and network capacity Word of mouth update experience (satisfaction or frustration) AB model of cell phone users generate load (inject entities) DE model of network infrastructure The AnyLogic Company 18

10 Example 4: Epidemic and clinic Pass infection request treatment (inject entity) notify agent (you ve been treated) AB model of population discard request (remove entity) DE model of clinic The AnyLogic Company 19

11 The choice of architecture and methods You can develop models: Simple or complex Flat or hirarchical Single-method or multi-method With unique or replicated components With static structure or with dynamically changing structure Hardcoded or configured from external data sources The model structure does reflect the structure of the system being modeled however, not "literally", but as seen from the problem viewpoint The choice of modeling method should be governed by the criterion of naturalness Compact, minimalistic, clean, beautiful, easy to understand and explain if the internal texture of your model is like that, then you chose the right method The AnyLogic Company 20

12 The problem of model boundary When developing, say, a discrete event model of: a supply chain, IT infrastructure, or a contact center (having chosen DE) the modeler would typically ask the client to provide: the arrival rates of the orders, transactions, or phone calls he would then be happy to get: some constant values, periodical patterns, or trends, and treat arrival rates as variables exogenous to the model In reality, however, those variables are outputs of another dynamic system, such as a market, or a user base Moreover, that other system can, in turn, be affected by the system being modeled The choice of the model boundary therefore is very important The only methodology that explicitly talks about the problem of model boundary is system dynamics However, the system dynamics modeling language is limited by its high level of abstraction, and many problems cannot be modeled with the necessary accuracy The AnyLogic Company 21

13 Thank you! Questions? Links: AnyLogic website: AnyLogic models online: The AnyLogic Company 22