An agent-based discrete event simulation approach for modeling large-scale disaster evacuation network

2014 ◽  
Author(s):  
Hyeong Suk Na ◽  
Amarnath Banerjee
Keyword(s):  
Discrete Event Simulation ◽  
Large Scale ◽  
Discrete Event ◽  
Simulation Approach ◽  
Agent Based ◽  
Event Simulation

scholarly journals DVCompute Simulator for discrete event simulation

2021 ◽  
Vol 16 (93) ◽  
pp. 93-108
Author(s):  
David E. Sorokin ◽  
Keyword(s):  
Discrete Event Simulation ◽  
Large Scale ◽  
Distributed Simulation ◽  
Discrete Event ◽  
Simulation Models ◽  
General Purpose ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Event Simulation ◽  
Programming Techniques

The author of this article represents his own work DVCompute Simulator, which is a collection of general-purpose programming libraries for discrete event simulation. The aim of the research was to create a set of simulators in the Rust language, efficient in terms of speed of execution, based on a unified approach and destined for different simulation modes. The simulators implement such modes as ordinary sequential simulation, nested simulation and distributed simulation. The article describes that nested simulation is related to Theory of Games, while distributed simulation can be used for running large-scale simulation models on supercomputers. It is shown how these different simulation modes can be implemented based on the single approach that combines many paradigms: the event-oriented paradigm, the process-oriented one, blocks similar to the GPSS language and even partially agent-based modeling. The author's approach is based on using the functional programming techniques, where the simulation model is defined as a composition of computations. The results of testing two modules are provided, where the modules support both the optimistic and conservative methods of distributed simulation.

scholarly journals Modeling Clinical Outcomes in Prostate Cancer: Application and Validation of the Discrete Event Simulation Approach

2018 ◽  
Vol 21 (4) ◽  
pp. 416-422 ◽  
Author(s):  
Feng Pan ◽  
Odette Reifsnider ◽  
Ying Zheng ◽  
Irina Proskorovsky ◽  
Tracy Li ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Outcomes ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Approach ◽  
Event Simulation

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.

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