The application of real-time spatial optimization in a Spatial Decision Support System, utilizing Geographic Information Science and Technology, is shown using the example of Wood Supply Chain management. Interdisciplinarity is a key concept, because Geographic Information Science, Operations Research and Spatial Decision Support Systems are bundled together. Service Oriented Architectures allow the development of an architecture that consists of several - even spatial - dispersed hard- and software. This approach guarantees a fail safe architecture and paves the way for Ubiquitous Computing and Spatial Data Infrastructures. In addition, spatial data can be gathered and sent out in real-time from/to mobile devices utilizing Location based Services. The dissertation proves, that a specific spatial problem can be solved using mathematical modeling and an appropriate optimization technique. In this work Adaptive Large Neighborhood Search is used. By the fact that the optimization is enveloped in a Spatial Decision Support System, decision makers are involved in the decision process. On the one hand they are able to alter model parameters which alter the optimization process at hand, and on the other hand they can choose one decision alternative recommended by the system. This dissertation shows - based on example of Wood Supply Chain management - that real-time spatial optimization is able to successfully "solve" a spatial problem when coupled with a Spatial Decision Support System.
- Quote paper
- Johannes Scholz (Author), 2010, Real-Time Spatial Optimization, Munich, GRIN Verlag, https://www.grin.com/document/165048
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