© yilmaz- - 2004-12-06 “introduction to discrete-event simulation” 1 introduction to...
DESCRIPTION
© Yilmaz “Introduction to Discrete-Event Simulation” 3 Aim The aim of this lecture is to overview the fundamentals, underlying principles, conceptual frameworks, and the life-cycle of a discrete-event simulation study.TRANSCRIPT
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© Yilmaz- - 2004-12-06 “Introduction to Discrete-Event Simulation” 1
Introduction to Discrete-Event Simulation
Dr. Levent YilmazM&SNet: Auburn M&S Laboratory
Computer Science & Software EngineeringAuburn University, Auburn, AL 36849http://www.eng.auburn.edu/~yilmaz
COMP8700 Agent-Directed Simulation
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Use of Simulation for Agents Use of Agents for Simulation
Agent Simulation: simulation of agent systems. Agent simulation is already used in several categories of application areas such as:- Engineering applications: electrical engineering, irrigation systems, manufacturing systems, mechatronics, networks, robotics, software, as well as transportation/logistics;- Management/economy applications: economy, e-commerce, and management;- Social systems and human behaviour applications: social systems, psychology/human behaviour, physiology, negotiation, and organization theory;- Environment applications: ecosystems, land use;- Military applications.
Agent-supported Simulation: use of agents in a simulation study for at least one of the following purposes: (in a computer-aided simulation environment –including simulation-based problem solving environments):- to provide computer assistance for front-end and/or back-end interface functions; - to process elements of a simulation study symbolically (for example, for consistency checks and built-in reliability); and- to provide cognitive abilities to the elements of a simulation study, such as learning or understanding abilities.Agent-based Simulation: use of agents for the generation of model behavior in a simulation study
Agent-Directed Simulation
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AimAim
• The aim of this lecture is to overview the fundamentals, underlying principles, conceptual frameworks, and the life-cycle of a discrete-event simulation study.
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• The initialization include the assignment of initial values to all the attributes.
• Fixed time increment is as the time flow mechanism.
• If an activity’s condition is satisfied, the actions of that activity are executed.
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• The three phase approach combines activity scanning and event scheduling frameworks.
• Unlike the two-phased approach the time flow mechanism implements a variable time increment approach.
• All B (bound to occur – unconditional) activities with occurrence times equal to the simulation clock are executed before activity scanning takes place.
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• Under this framework the life cycle of an object that moves through and interacts with the processes of the system is represented.
• Initialization phase creates the attributes and dynamic objects.
• In the clock update phase the time is advanced to the move time of the front-end object of the FOL.
• All objects with equivalent move time are transferred to COL, which is processed in the scan phase.
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• Problem formulation is the process by which the initially communicated problem is translated into a formulated problem sufficiently well defined to enable specific research action.
• Not enough attention is given in the life cycle.
• The accuracy of problem formulation greatly affects the acceptability and credibility of simulation results.
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