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Hoeger, Herbert R.; Jones, Douglas W.
doi: 10.1177/003754979606700502pmid: N/A
There have been many attempts to apply parallel computers to discrete-event simulation. These may be divided into two main approaches, distributed simulation and concurrent simulation. Distributed simulation relies on a spatial decomposition and partitions the simulation model into components that can be executed on different processors. Concurrent simulation is based on a temporal decomposition.This paper focuses on the integration of these two approaches; we call our result an integrated conservative distributed concurrent simulator. This is a distributed simulator with concurrency added to each model component. To do so, a shared- memory environment was used, and both approaches were unified to an event- centered view. We also partitioned the global concurrent pending-event set of the concurrent simulator and provided each model component in the distributed simulator with a local concurrent pending-event set, allowing us to add concurrency to each model component.
Fishwick, Paul A.; Kim, Gyooseok; Jin Joo Lee,
doi: 10.1177/003754979606700503pmid: N/A
Real-time military planning and decision making involve several different modeling techniques, including rule-based, operator-based, and dynamic-model based approaches. While rule-based approaches are generally fast and are more appropriate for simple scenarios, simulation methods and dynamic models, indigenous to the simulation literature, are necessary to plan within environments involving large-scale uncertainty, multiple interacting elements and complex dynamics. Planning techniques must inter-operate to yield the best decisions, and we have found that simulation-based planning serves as an architecture for detailed model levels for both real-time and off-line decision making. We introduce simulation-based planning as a methodology for addressingthe complexity involved in Air Force missions while employing an example of air interdiction.
doi: 10.1177/003754979606700504pmid: N/A
In the last few years, a concept for automating Load-Haul-Dump (LHD) vehicles has stimulated considerable interest in the world mining industry. In this concept, the tramming and dumping operations of an LHD should be automatic. During loading, an operator from a control room fills the bucket of a vehicle via remote- control aided by a television system. The application of such a Remote-controlled/ Automatic LHD (RAL) system in underground hard rock mines exhibits some operational and traffic control characteristics that have not been studied previously in mining (e.g., vehicle motion in bidirectional lane segments). This paper presents a discrete-event simulation model developed for studying and evaluating the operation of a fleet of RALs. This model integrates graphical modeling and presentation of RAL transport layouts with animation of the motion of vehicles during simulation. The model is used to evaluate the capacity of a future fleet of RALs which can operate in a typical transport layout at the LKAB Swedish iron ore mine in Kiruna.
doi: 10.1177/003754979606700505pmid: N/A
Two examples of models formulated in terms of the Ordinary Differential Equations (ODE) are given. It is pointed out that, in certain situations, the ODE- based models commonly used in system dynamics may be completely wrong. Even in some very simple models of the dynamics of populations it is not certain that any finite state vector of the system exists, which means that the corresponding finite ODE model does not exist. If the modeled system is nonlinear, the existence of solutions to the ODE model is important. The mapping from the space of disturbances to the space of corresponding trajectories may be discontinuous, even if the right-hand sides of the equations are continuous. This may cause errors when simplified models are used. A possible application of the discrete event and object-oriented simulation instead of the ODE models is suggested.
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