New Hydro-economic System Dynamics and Agent-based Modeling for Sustainable Urban Groundwater Management: A Case Study of Dehno, Yazd Province, Iran

2021 ◽  
pp. 103078
Author(s):  
Mohammad Ali Arasteh ◽  
Yaghoub Farjami
Keyword(s):  
System Dynamics ◽  
Economic System ◽  
Groundwater Management ◽  
Urban Groundwater ◽  
Agent Based Modeling ◽  
Agent Based

scholarly journals Elements for the Agent-Based Modeling of Slavery Systems

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Antõnio C R Costa
Keyword(s):  
Economic System ◽  
Agent Based Modeling ◽  
Free Labor ◽  
Agent Based ◽  
System A ◽  
First Case ◽  
Formal Concepts ◽  
Economic Relationship ◽  
South Of Brazil

This paper introduces formal concepts for the agent-based modeling of slavery systems. The concepts of master-slave economic relationship, slavery-based economic system, slavery-supporting legal system, and slavery-based material agent society are formally defined. A first case study recasts, for material agent societies, North \& Thomas' economic model determining the objective conditions under which it is rational for a society to choose a slavery-based economic system over a free labor-based economic system. A second case study makes use of elements of F. H. Cardoso's study of slavery in the south of Brazil to illustrate the application of the formal concepts introduced in the paper.

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.

An agent-based modeling approach to predict the evolution of market share of electric vehicles: A case study from Iceland

2012 ◽  
Vol 79 (9) ◽  
pp. 1638-1653 ◽  
Author(s):  
Ehsan Shafiei ◽  
Hedinn Thorkelsson ◽  
Eyjólfur Ingi Ásgeirsson ◽  
Brynhildur Davidsdottir ◽  
Marco Raberto ◽  
...  
Keyword(s):  
Market Share ◽  
Electric Vehicles ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Modeling Approach

scholarly journals Agent-Based and System Dynamics Modeling of Water Field Services

Challenges ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 13
Author(s):  
Bernard Amadei
Keyword(s):  
System Dynamics ◽  
Computational Models ◽  
Software Modeling ◽  
Dynamics Modeling ◽  
Water Utility ◽  
Modeling Tools ◽  
Agent Based ◽  
Water Field ◽  
The Individual

This paper explores the applicability of the agent-based (AB) and system dynamics (SD) methods to model a case study of the management of water field services. Water borehole sites are distributed over an area and serve the water needs of a population. The equipment at all borehole sites is managed by a single water utility that has adopted specific repair, replacement, and maintenance rules and policies. The water utility employs several service crews initially stationed at a single central location. The crews respond to specific operation and maintenance requests. Two software modeling tools (AnyLogic and STELLA) are used to explore the benefits and limitations of the AB and SD methods to simulate the dynamic being considered. The strength of the AB method resides in its ability to capture in a disaggregated way the mobility of the individual service crews and the performance of the equipment (working, repaired, replaced, or maintained) at each borehole site. The SD method cannot capture the service crew dynamics explicitly and can only model the average state of the equipment at the borehole sites. Their differences aside, both methods offer policymakers the opportunity to make strategic, tactical, and logistical decisions supported by integrated computational models.

scholarly journals Approaches to Modeling the Gas-Turbine Maintenance Process

2011 ◽  
Vol 12 (1) ◽  
Author(s):  
Tai-Tuck Yu ◽  
James P. Scanlan ◽  
Richard M. Crowder ◽  
Gary B. Wills
Keyword(s):  
Decision Making ◽  
Gas Turbine ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Event Modeling ◽  
Human Decision ◽  
Event Model ◽  
Discrete Event Model

Discrete-event modeling has long been used for logistics and scheduling problems, while multi-agent modeling closely matches human decision-making process. In this paper, a metric-based comparison between the traditional discrete-event and the emerging agent-based modeling approaches is reported. The case study involved the implementation of two functionally identical models based on a realistic, nontrivial, civil aircraft gas turbine global repair operation. The size, structural complexity, and coupling metrics from the two models were used to gauge the benefits and drawbacks of each modeling paradigm. The agent-based model was significantly better than the discrete-event model in terms of execution times, scalability, understandability, modifiability, and structural flexibility. In contrast, and importantly in an engineering context, the discrete-event model guaranteed predictable and repeatable results and was comparatively easy to test because of its single-threaded operation. However, neither modeling approach on its own possesses all these characteristics nor can each handle the wide range of resolutions and scales frequently encountered in problems exemplified by the case study scenario. It is recognized that agent-based modeling can emulate high-level human decision-making and communication closely while discrete-event modeling provides a good fit for low-level sequential processes such as those found in manufacturing and logistics.

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