scholarly journals Approaching Industrial Symbiosis Through Agent-Based Modeling and System Dynamics

2018 ◽  
pp. 171-185 ◽  
Author(s):  
Melissa Demartini ◽  
Flavio Tonelli ◽  
Filippo Bertani
Keyword(s):  
System Dynamics ◽  
Agent Based Modeling ◽  
Industrial Symbiosis ◽  
Agent Based

Multi-Methodology Approach

2021 ◽  
pp. 98-128
Keyword(s):  
System Dynamics ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Multiple Methods ◽  
Soft Systems ◽  
Agent Based ◽  
Event Simulation ◽  
Pluralistic Approach ◽  
The Difference

The pluralistic approach in today's world needs combining multiple methods, whether hard or soft, into a multi-methodology intervention. The methodologies can be combined, sometimes from several different paradigms, including hard and soft, in the form of a multi-methodology so that the hard paradigms are positivistic and see the organizational environment as objective, while the nature of soft paradigms is interpretive. In this chapter, the combination of methodologies has been examined using soft systems methodologies (SSM) and simulation methodologies including discrete event simulation (DES), system dynamics (SD), and agent-based modeling (ABM). Also, using the ontological, epistemological, and methodological assumptions underlying the respective paradigms, the difference between SD, ABM, SSM; a synthesis of SSM and SD generally known as soft system dynamics methodology (SSDM); and a promising integration of SSM and ABM referred to as soft systems agent-based methodology (SSABM) have been proven.

Simulation modeling of the smart city system: The concept, methods, and cases

2020 ◽  
Vol 19 (2) ◽  
pp. 226-250 ◽  
Author(s):  
V.L. Makarov ◽  
R.A. Bakhtizin ◽  
G.L. Beklaryan ◽  
A.S. Akopov
Keyword(s):  
Decision Making ◽  
Urban Planning ◽  
System Dynamics ◽  
Smart City ◽  
Simulation Modeling ◽  
Simulation Models ◽  
Agent Based Modeling ◽  
Decision Making Process ◽  
Agent Based ◽  
City System

Subject. The research investigates key processes of urban life and its maintenance, including food supply, infrastructure, fire security, quality and accessibility of medical services, etc. The article also discusses the creation of a system supporting the Smart City decision-making process. Objectives. The research develops methods and tools to manage the Smart City system through system dynamics and agent-based modeling. Methods. Using simulation modeling, namely system dynamics and agent-based modeling (supported via Powersim and AnyLogic), we evaluate how multiple guiding parameters influence crucial characteristics of the Smart City system. Results. We devised an approach to designing the Smart City system through methods of system dynamics and agent-based modeling (supported via Powersim and AnyLogic) intended to streamline the decision making process for reasonable urban planning. Conclusions and Relevance. We propose the consolidated architecture of the Smart City decision-making system integrating the simulation models, data storage and city monitoring subsystem. The article describes the cases of simulation models implemented via Powersim and AnyLogic to support rational urban planning. The simulation models will significantly improve the quality of urban environment, satisfy the demand for food products, provide access to healthcare services and ensure effective rescue actions in case of emergency.

An Epistemological Gap in Simulation Technologies and the Science of Society

2011 ◽  
pp. 114-135
Author(s):  
Martin Neumann
Keyword(s):  
System Dynamics ◽  
Sociological Theory ◽  
Agent Based Modeling ◽  
Social Simulation ◽  
Methodological Framework ◽  
Methodological Issues ◽  
Top Down ◽  
Agent Based ◽  
Simulation Methodology ◽  
Contrasting Agent

This chapter addresses methodological issues in relation to simulation technologies, using the example of archaeological modeling. While the top-down architecture of system dynamics became popular in the 1970s, the bottom-up approach of agent-based modeling actually predominates in social simulation. This paper demonstrates that the gap in sociological theory between interactionalist and structuralist theories can be discerned in the methodological framework. The theoretical implications associated with the choice of a simulation methodology are examined by contrasting agent-based and equation-based models in detail. This example makes evident how intimately issues of methodology are interwoven with epistemological and ontological questions. However, agent-based modeling aims precisely to overcome this dichotomy with the notion of emergence. The chapter therefore concludes with an overview of requirements for a technology of emergence.

scholarly journals System Dynamics versus Agent-Based Modeling: A Review of Complexity Simulation in Construction Waste Management

2018 ◽  
Vol 10 (7) ◽  
pp. 2484 ◽  
Author(s):  
Zhikun Ding ◽  
Wenyan Gong ◽  
Shenghan Li ◽  
Zezhou Wu
Keyword(s):  
Waste Management ◽  
System Dynamics ◽  
Complex Adaptive System ◽  
Agent Based Modeling ◽  
Effective Management ◽  
Construction Waste ◽  
Agent Based ◽  
Complex Adaptive ◽  
Research Findings ◽  
Novel Model

The environmental impacts caused by construction waste have attracted increasing attention in recent years. The effective management of construction waste is essential in order to reduce negative environmental influences. Construction waste management (CWM) can be viewed as a complex adaptive system, as it involves not only various factors (e.g., social, economic, and environmental), but also different stakeholders (such as developers, contractors, designers, and governmental departments) simultaneously. System dynamics (SD) and agent-based modeling (ABM) are the two most popular approaches to deal with the complexity in CWM systems. However, the two approaches have their own advantages and drawbacks. The aim of this research is to conduct a comprehensive review and develop a novel model for combining the advantages of both SD and ABM. The research findings revealed that two options can be considered when combining SD with ABM; the two options are discussed.

Simulation of management systems of forest infrastructure

2015 ◽  
Vol 5 (2) ◽  
pp. 177-187
Author(s):  
Васильев ◽  
Oleg Vasilyev ◽  
Корныльева ◽  
Yuliya Kornylyeva
Keyword(s):  
System Dynamics ◽  
Discrete Event Simulation ◽  
Input Data ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Management Systems ◽  
Center Problem ◽  
Management Tools ◽  
Agent Based ◽  
Event Simulation

The article considers the possibility of a modern and rapidly developing management tools – simulation, allows to obtain detailed statistics on various aspects of the system, depending on the input data. The basic modeling approaches: system dynamics, discrete-event simulation, and agent-based modeling. Forestry breeding and seed center problem to be solved with the help of simulation are substantiated. Examples of problems in other areas of forestry, which can be solved with the help of this tool, are given.

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