• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Agent-based modeling, System Dynamics or Discrete-event Simulation; Modeling Paradigm for Supply Chains Simulation
 

Agent-based modeling, System Dynamics or Discrete-event Simulation; Modeling Paradigm for Supply Chains Simulation

on

  • 2,083 views

Each simulation paradigm is characterized by a set of core assumptions and some underlying concepts to describe the world. These assumptions, in fact, constrain the development of a conceptual model ...

Each simulation paradigm is characterized by a set of core assumptions and some underlying concepts to describe the world. These assumptions, in fact, constrain the development of a conceptual model for the system of study. Consequently, the choice of appropriate simulation paradigm is an important step in the model development process. In this paper, selection of a simulation approach for supply chain modeling is discussed. For this purpose, the supply chain is described from perspective of two well-established system theories. Firstly, supply chains are defined as socio-technical systems. Afterwards, they are described from complex adaptive systems perspective. This study gives a set of features for supply chains as complex socio-technical systems which is subsequently used to compare three simulation paradigms for supply chain modeling -- namely, system dynamics, discrete-even simulation and agent-based simulation.

Statistics

Views

Total Views
2,083
Views on SlideShare
2,064
Embed Views
19

Actions

Likes
0
Downloads
31
Comments
2

2 Embeds 19

http://www.linkedin.com 16
https://www.linkedin.com 3

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel

12 of 2 previous next

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • Each paradigm is characterized by a set of core – or fundamental - assumptions and some underlying concepts (Lorenz and Jost, 2006) or, as Meadows and Robinson (1985, p. 17) explain, “every modeling discipline depends on unique underlying assumptions; that is, each modeling method is itself based on a model of how modeling should be done”. For example, when a modeler selects System Dynamics as a simulation paradigm, he explicitly assumes that “the world is made up of rates, levels and feedback loops” (Meadows, 1989). The types of assumptions brought by selection of a particular modeling and simulation paradigm are also called “heroic assumptions” by North and Macal (2007). The existence of these assumptions in each simulation paradigm implies that selection of a modeling paradigm is part of the conceptualization process in a simulation study.
  • that it might not be necessary to capture all complexity dimensions of a supply chain in every modeling effort; however, when we choose a simulation paradigm or when we make some simple assumptions to reduce the complexity of a system in the model development process, we must be fully aware of complexity dimensions that are influenced by decisions we make

Agent-based modeling, System Dynamics or Discrete-event Simulation; Modeling Paradigm for Supply Chains Simulation Agent-based modeling, System Dynamics or Discrete-event Simulation; Modeling Paradigm for Supply Chains Simulation Presentation Transcript

  • Evaluation of Paradigms forModeling Supply Chains as Complex Socio-technical Systems Behzad Behdani Faculty of Technology, Policy and Management Delft University of Technology
  • Outline• Role of simulation paradigm in each simulation study• Supply chains as socio-technical systems• Supply chains as complex adaptive systems• Comparison of simulation paradigms for supply chain simulation• Concluding remarks
  • Role of simulation paradigm in each simulation study Conceptual model: • Inputs (experimental factors) • Outputs (responses) • Model content (assumptions an simplificationsRobinson, S. (2004). Simulation: The Practice of Model Development and Use. Wiley.
  • Role of simulation paradigm in each simulation study• Meadows and Robinson (1985, p. 17): “every modeling discipline depends on unique underlying assumptions; that is, each modeling method is itself based on a model of how modeling should be done”.• For example, by selecting System Dynamics we implicitly assume that: “the world is made up of rates, levels and feedback loops” (Meadows, 1989).- Meadows, D. and Robinson, J. (1985). The Electronic Oracle: Computer Models and Social Decisions, John Wiley & Sons- Meadows, D.H. (1989). System dynamics meets the press, System Dynamics Review 5(1): 68-80.
  • Role of simulation paradigm in each simulation study• Therefore: – Selection of simulation paradigm constrains developing a conceptual model for a system. – In model development process a simulation paradigm must be selected which is the best fit with system and provide the highest degree of flexibility to capture system characteristics.
  • Supply chains as socio-technical systems • From ST system theory perspective: • The system behavior can be analyzed (and improved) only by considering both social and technical subsystems and the interdependencies between them (Ottens etal. 2006).Ottens, M., M. Franssen, P. Kroes, and I. Van De Poel. 2006. “Modelling Infrastructures as Socio-technicalSystems.” International Journal of Critical Infrastructures 2: 133-145.
  • Supply chains as complex adaptive systemsA complex adaptive system is a system that emerges over timeinto a coherent form, and adapts and organizes itself withoutany singular entity deliberately managing or controlling it(Holland 1996). Macro-level Complexity System-Level Micro-level Complexity Individal-LevelHolland, J.H. 1996. Hidden Order: How Adaptation Builds Complexity. Addison-Wesley.
  • Supply chains as complex adaptive systems• Micro-level properties: – Numerousness and heterogeneity – Local Interactions – Nestedness – Adaptiveness
  • Supply chains as complex adaptive systems• Macro-level properties: – Emergence – Self-organization – Co-evolution – Path dependency
  • Comparison of simulation paradigms for supply chain simulationSystem Dynamics (SD) Discrete-event Simulation (DES) Agent-based Simulation Individual-oriented; focus is onSystem-oriented; focus is on modeling Process-oriented; focus is on modeling modeling the entities and interactionsthe system observables the system in detail between themHomogenized entities; all entities areassumed have similar features; Heterogeneous entities Heterogeneous entitiesworking with average values Micro-level entities are passive Micro-level entities are active entities ‘objects’ (with no intelligence orNo representation of micro-level (agent) that can make sense the decision making capability) that moveentities environment, interact with others and through a system in a pre-specified make autonomous decisions processDriver for dynamic behavior of system Driver for dynamic behavior of system Driver for dynamic behavior of systemis "feedback loops". is "event occurrence". is “agents decisions & interactions".Mathematical formalization of system Mathematical formalization of system Mathematical formalization of systemis in “Stock and Flow” is with “Event, Activity and Process”. is by “Agent and Environment”handling of time is continuous (and handling of time is discrete handling of time is discretediscrete) Experimentation by changing theExperimentation by changing the Experimentation by changing the agent rules (internal/interaction rules)system structure process structure and system structureSystem structure is fixed The process is fixed The system structure is not fixed
  • Comparison of simulation paradigms for supply chain simulation Discrete-event Simulation System Dynamics (SD) (DES) Agent-based Simulation No distinctive entities; distinctive and distinctive andNumerousness and working with average heterogeneous entities in heterogeneous entities inheterogeneity system observables both technical and social the technical level (homogenous entities) level Average value for Interactions in technical Interactions in both socialLocal Interactions interactions level and technical levelNestedness Hard to present Not usually presented Straightforward to present No adptiveness at No adptiveness at Adaptiveness as agentAdaptiveness individual level individual level property
  • Comparison of simulation paradigms for supply chain simulation Discrete-event Simulation System Dynamics (SD) (DES) Agent-based Simulation Capable to capture Debatable because of lack Debatable because of pre- because of modelingEmergence of modeling more than designed system system in two distinctive one system level properties levels Hard to capture due to Hard to capture due to Capable to captureSelf-organization lack of modeling the lack of modeling the because of modeling individual decision making individual decision making autonomous agents Capable to capture Hard to capture because Hard to capture because because network structureCo-evolution system structure is fixed processes are fixed is modified by agents interactions Capable to capture Debatable because of no Debatable because of no because current and explicit consideration of explicit consideration ofPath dependency future state can be history to determine history to determine explicitly defined based on future state future state system history
  • Concluding remarks• Each simulation paradigm is characterized by a set of core assumptions and some underlying concepts to describe the world. These assumptions constrain the development of a conceptual model for the system of study.• Selection of an appropriate modeling paradigm is absent in most of presented procedures for simulation studies.
  • Concluding remarks• It might not be necessary to capture all complexity dimensions of a supply chain in every modeling effort; however, we must be aware how selection of simulation paradigm impacts (constrains) our model development.• The discussions in this paper is not ABM is always the best option; especially in the model coding step. ABM has also its drawbacks!• The arguments in this paper can be valid for other complex ST systems.
  • A copy of paper can be found in: http://dl.acm.org/citation.cfm?id=2430294 http://www.academia.edu/1523272/Evaluati on_of_Paradigms_for_Modeling_Supply_Cha ins_as_Complex_Socio-Technical_Systems You can also find me on: behzadb09@gmail.com15