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.

scholarly journals Methods for Weighting Decisions to Assist Modelers and Decision Analysists: A Review of Ratio Assignment and Approximate Techniques

2021 ◽  
Vol 11 (21) ◽  
pp. 10397
Author(s):  
Barry Ezell ◽  
Christopher J. Lynch ◽  
Patrick T. Hester
Keyword(s):  
Decision Making ◽  
Discrete Event Simulation ◽  
Computational Models ◽  
State Of The Art ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Decision Makers ◽  
Agent Based ◽  
Event Simulation ◽  
Decision Making Processes

Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques that serve as options for reaching unique decisions based on personally and individually ranked criteria. These techniques are organized into a taxonomy of ratio assignment and approximate techniques, and the strengths and limitations of each are explored. We compare these techniques potential uses across the Agent-Based Modeling (ABM), System Dynamics (SD), and Discrete Event Simulation (DES) modeling paradigms to inform current researchers, students, and practitioners on the state-of-the-art and to enable new researchers to utilize methods for modeling multi-criteria decisions.

METHODOLOGY OF CONSTRUCTING THE CONCEPTUAL COVID-19 SPREADING MODELS TO DRAW CONCLUSIONS REGARDING THE INFECTION RISKS

2021 ◽  
Vol 55 (4) ◽  
pp. 23-35
Author(s):  
A.V. Polyakov ◽  
◽  
Yu.A. Bubeev ◽  
V.М. Usov ◽  
B.М. Vladimirsky ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Health Care Professionals ◽  
Infection Prevention ◽  
Agent Based Modeling ◽  
Verbal Information ◽  
Agent Based ◽  
Event Modeling ◽  
Coronavirus Infection ◽  
Information Objects

Drawing conclusions about the coronavirus infection risks and real-time decision-making is a primary duty of health-care professionals. The agent-based modeling of events allows look closely at expectable hazards and paths of immediate infection as the grounds for planning personal tactics of infection prevention. The event modeling transforms verbal information (objects, relations, factors etc.) in constructs of knowledge for computer analysis of COVID-19 contagion. The knowledge constructs or information ontology may be helpful to health-care professionals in bringing to people of risky occupations true information of hazards and validity of the existing rules and regulations.

A Language for Agent-based Discrete-event Modeling and Simulation of Linked Lives

2022 ◽  
Vol 32 (1) ◽  
pp. 1-26
Author(s):  
Oliver Reinhardt ◽  
Tom Warnke ◽  
Adelinde M. Uhrmacher
Keyword(s):  
Modeling And Simulation ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Domain Specific ◽  
Event Modeling ◽  
Linked Lives ◽  
External Domain ◽  
Concrete Language

In agent-based modeling and simulation, discrete-time methods prevail. While there is a need to cover the agents’ dynamics in continuous time, commonly used agent-based modeling frameworks offer little support for discrete-event simulation. Here, we present a formal syntax and semantics of the language ML3 (Modeling Language for Linked Lives) for modeling and simulating multi-agent systems as discrete-event systems. The language focuses on applications in demography, such as migration processes, and considers this discipline’s specific requirements. These include the importance of life courses being linked and the age-dependency of activities and events. The developed abstract syntax of the language combines the metaphor of agents with guarded commands. Its semantics is defined in terms of Generalized Semi-Markov Processes. The concrete language has been realized as an external domain-specific language. We discuss implications for efficient simulation algorithms and elucidate benefits of formally defining domain-specific languages for modeling and simulation.

scholarly journals Simulating Army Rail Yard Operations at the Port of Bremerhaven

2019 ◽  
Vol 6 (2) ◽  
pp. 95-100
Author(s):  
Joshua Bieger ◽  
Jadalaine Ferrer ◽  
Dillon Riedlinger ◽  
William Xu ◽  
Jeffrey Demarest
Keyword(s):  
Discrete Event ◽  
The United States ◽  
Network System ◽  
Operational Experience ◽  
Military Operations ◽  
Engineer Research ◽  
Event Simulation ◽  
Event Model ◽  
Discrete Event Model

To maintain the United States military’s capability to deploy rapidly across the globe, logistical planning tools, simulations, and models enhance leaders’ decision making abilities. This research develops a discrete event model designed to simulate military operations within a railyard in order to support the Engineer Research and Development Center’s (ERDC) Planning Logistics Analysis Network System (PLANS). The research team chose the Port of Bremerhaven, Germany as a case study due to its relevance to current military operations, granting us access to timely data and stakeholders with recent operational experience. The discrete event simulation (DES) utilizes stochastic processes and multiple layouts in order to analyze the amount of time it takes to move varying amounts of cargo and vehicles and identify potential bottlenecks in the operation.

scholarly journals Theoretical foundations of human decision-making in agent-based land use models – A review

2017 ◽  
Vol 87 ◽  
pp. 39-48 ◽  
Author(s):  
J. Groeneveld ◽  
B. Müller ◽  
C.M. Buchmann ◽  
G. Dressler ◽  
C. Guo ◽  
...  
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Agent Based ◽  
Human Decision ◽  
Land Use Models ◽  
Theoretical Foundations

Hierarchical Bayesian Parameter Estimation for Modeling and Analysis of User Affective Influence

2013 ◽  
Author(s):  
Feng Zhou ◽  
Jianxin (Roger) Jiao
Keyword(s):  
Decision Making ◽  
Interior Design ◽  
Computational Models ◽  
Human Perception ◽  
Model Parameters ◽  
Hierarchical Bayesian ◽  
Affective States ◽  
Modeling And Analysis ◽  
Human Decision

Traditional user experience (UX) models are mostly qualitative in terms of its measurement and structure. This paper proposes a quantitative UX model based on cumulative prospect theory. It takes a decision making perspective between two alternative design profiles. However, affective elements are well-known to have influence on human decision making, the prevailing computational models for analyzing and simulating human perception on UX are mainly cognition-based models. In order to incorporate both affective and cognitive factors in the decision making process, we manipulate the parameters involved in the cumulative prospect model to show the affective influence. Specifically, three different affective states are induced to shape the model parameters. A hierarchical Bayesian model with a technique called Markov chain Monte Carlo is used to estimate the parameters. A case study of aircraft cabin interior design is illustrated to show the proposed methodology.

Sign in / Sign up

Export Citation Format

Share Document