New manufacturing modeling methodology: data driven design and simulation system based on XML
Proceedings of the 35th conference on Winter simulation: driving innovation
Ontologies for modeling and simulation: issues and approaches
WSC '04 Proceedings of the 36th conference on Winter simulation
Potential modeling and simulation applications of the web ontology language - OWL
WSC '04 Proceedings of the 36th conference on Winter simulation
Simulation optimization: a review, new developments, and applications
WSC '05 Proceedings of the 37th conference on Winter simulation
Using ontologies for simulation modeling
Proceedings of the 38th conference on Winter simulation
From domain ontologies to modeling ontologies to executable simulation models
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
Supporting interoperability using the discrete-event modeling ontology (DeMO)
Winter Simulation Conference
Feasibility study for automatic calibration of transportation simulation models
Proceedings of the 44th Annual Simulation Symposium
| Hi-index | 0.00 |
Simulation has become a widely accepted technology for analyzing or planning systems in various domains. In production logistics, for instance, many companies use simulation to evaluate scenarios before actually the construction or modifications of the production hall or processes are performed in order to get insights about the performance of planned configurations. In this paper, we propose an approach to knowledge-based adaptation of simulation models. The vision of this work is to go one step beyond parameter optimization, namely to provide means for automated structural changes in simulation models, and thus for the generation of simulation model variants. For a first evaluation of our approach, we introduce a system consisting of a simulation control as well as a model adaptation module with a set of adaptation operations. Our implementation is coupled to the simulation system Plant Simulation in order to perform simulation runs. For illustration we apply our system to a test scenario and present first results.