Combined discrete event continuous systems simulation

SIMULATION ◽  
1970 ◽  
Vol 14 (2) ◽  
pp. 61-72 ◽  
Author(s):  
David Arthur Fahrland
Keyword(s):  
Discrete Event ◽  
Continuous Systems ◽  
Systems Simulation

Discrete-Event Systems Simulation.

1985 ◽  
Vol 36 (5) ◽  
pp. 455
Author(s):  
Brian Hollocks ◽  
Jerry Banks ◽  
John S. Carson II
Keyword(s):  
Discrete Event Systems ◽  
Discrete Event ◽  
Event Systems ◽  
Systems Simulation

scholarly journals Simulation Project for Logistics of Brazilian Soybean Exportation

2020 ◽  
Vol 19 (4) ◽  
pp. 571-582
Author(s):  
H. S. Lopes ◽  
R. S. Lima ◽  
F. Leal
Keyword(s):  
Integrated Management ◽  
Discrete Event ◽  
International Market ◽  
Simulation Method ◽  
Strategic Analysis ◽  
Logistics System ◽  
Logistics Systems ◽  
Event Simulation ◽  
Global Logistics ◽  
Systems Simulation

Decision-making in complex logistics systems involves high risks and associated impacts. A way to forecast the impacts of these decisions is through the use of systems simulation projects, where the systematic impacts of the parameters can be visualized. This study presents a project based on Discrete-Event Simulation (DES) that analyses Brazilian soybean export logistics from producing regions to main international customers. The strategic analysis of a global logistics system using DES is a particularity of this study. At the conception stage, the conceptual modelling was made using IDEF-SIM (Integrated Definition Methods – Simulation) method, which allowed a better abstraction of reality and more accurate model implementation. The experimental analysis took place through the construction of 39 scenarios with specific characteristics that verified system behaviours through proposed changes. The analyses and decisions are based on costs. The simulations indicated the necessity for: a) an integrated management between the systems agents; b) the development of internal transportation infrastructure, especially railways and waterways, to increase competitiveness of Brazilian soybeans in the international market.

Methodologies and Approaches in Discrete Event Simulation

2008 ◽  
pp. 1-35
Author(s):  
Evon M. O. Abu-Taieh ◽  
Asim Abdel Rahman El Sheikh
Keyword(s):  
Discrete Event ◽  
Activity Cycle ◽  
Scale Model ◽  
Discrete Events ◽  
Web Based ◽  
Event Simulation ◽  
Modeling Approaches ◽  
Continuous Models ◽  
Systems Simulation ◽  
Cycle Diagram

This chapter aims to give a comprehensive explanatory platform of simulation background. As this chapter comprises of four sections, it reviews simulation definitions, forms of models, the need for simulation, simulation approaches and modeling notations. Simulation definition is essential in order to set research boundaries. Moreover, the chapter discusses forms of models: scale model of the real system, or discrete and continuous models. Subsequently, the chapter states documentation of several reasons by different authors pertaining to the question of “why simulate?,” followed by a thorough discussion of modeling approaches in respect to general considerations. Simulation modeling approaches are discussed with special emphasis on the discrete events type only: process-interaction, event scheduling, and activity scanning, yet, a slight comparison is made between the different approaches. Furthermore, the chapter discusses modeling notations activity cycle diagram (ACD) with different versions of the ACD. Furthermore, the chapter discusses petri nets, which handle concurrent discrete events dynamic systems simulation. In addition, Monte Carlo simulation is discussed due to its important applications. Finally, the fourth section of this chapter reviews Web-based simulation, along with all three different types of object-oriented simulation and modeling.

scholarly journals Multiplicative Decomposition of Heterogeneity in Mixtures of Continuous Distributions

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 858
Author(s):  
Abraham Nunes ◽  
Martin Alda ◽  
Thomas Trappenberg
Keyword(s):  
Composite System ◽  
Discrete Event ◽  
Mixture Distributions ◽  
Continuous Systems ◽  
Multiplicative Decomposition ◽  
Composite Systems ◽  
Continuous Mixture ◽  
Hill Numbers ◽  
Continuous Setting ◽  
Non Parametric

A system’s heterogeneity (diversity) is the effective size of its event space, and can be quantified using the Rényi family of indices (also known as Hill numbers in ecology or Hannah–Kay indices in economics), which are indexed by an elasticity parameter q≥0. Under these indices, the heterogeneity of a composite system (the γ-heterogeneity) is decomposable into heterogeneity arising from variation within and between component subsystems (the α- and β-heterogeneity, respectively). Since the average heterogeneity of a component subsystem should not be greater than that of the pooled system, we require that γ≥α. There exists a multiplicative decomposition for Rényi heterogeneity of composite systems with discrete event spaces, but less attention has been paid to decomposition in the continuous setting. We therefore describe multiplicative decomposition of the Rényi heterogeneity for continuous mixture distributions under parametric and non-parametric pooling assumptions. Under non-parametric pooling, the γ-heterogeneity must often be estimated numerically, but the multiplicative decomposition holds such that γ≥α for q>0. Conversely, under parametric pooling, γ-heterogeneity can be computed efficiently in closed-form, but the γ≥α condition holds reliably only at q=1. Our findings will further contribute to heterogeneity measurement in continuous systems.

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