Hybrid simulation comes in many shapes and forms. It has been argued by many researchers that hybrid simulation provides a better insight of the system in hand as it allows modelers to assess its inherent problems from different dimensions. As a result Hybrid Simulation is becoming an important field within the Modeling and Simulation arena. Yet we find that there no clear and cohesive definition for it. Therefore, this panel paper aims to explore the concept of Hybrid Simulation and its progression through the years. In doing so, we hope to lay out the underpinnings of a structured Hybrid Simulation approach by providing historical narratives of the origins of hybrid models; the current challenges expressed by scholars; and future studies to ensure more focused development of a comprehensive methodology for Hybrid Simulation.
Simulation is introduced in terms of its different forms and uses, but the focus on discrete event modeling for systems analysis is dominant as it has been during the evolution of the technique within operations research and the management sciences. This evolutionary trace of over almost fifty years notes the importance of bidirectional influences with computer science, probability and statistics, and mathematics. No area within the scope of operations research and the management sciences has been affected more by advances in computing technology than simulation. This assertion is affirmed in the review of progress in those technical areas that collectively define the art and science of simulation. A holistic description of the field must include the roles of professional societies, conferences and symposia, and publications. The closing citation of a scientific value judgment from over 30 years in the past hopefully provides a stimulus for contemplating what lies ahead in the next 50 years.
Effective development environments for discrete event simulation models should reduce development costs and impro,ue model performance. A model specification language used in a model development environment is defined. This approach is intended to reduce modeling costs by interposing an intermediate form between a conceptual model (the model as it exists in the mind of the modeler) and an executable representation of that model. As a model specification is constructed, the incomplete specification can be analyzed to detect some types of errors and to provide some types of model documentation. The primitives used in this specification language, called a condition specification (CS), are carefully defined. A specification for the classical patrolling repairman model is used to illustrate this language. Some possible diagnostics and some untestable model specification properties, based on such a representation, are summarized.
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