Finding optimum route of electrical energy transmission line using multi-criteria with Q-learning

Due to an increasing energy requirement the consideration of route determination is becoming important. The aim of this project is to find an optimum result considering its important criteria. Finding an optimum route is a complex problem. It does not mean the shortest path to the problem. It is important to find the best way under the criterion that is determined by experts. Because of this we did not use the classical shortest path algorithm and we applied one of algorithms of the Artificial Intelligence. In this work, Geographic Information System (GIS)-based energy transmission route planning had been performed. In this optimization, using Multiagent Systems (MAS) which is a subdirectory of Distributed Artificial Intelligence the multi-criteria affecting energy transmission line (ETL) had been severally analyzed. The application had been actualized on the Selcuk University Campus Area. Therefore, the digital map of the campus area particularly had been composed containing of relevant criteria. Using Qlearning Algorithm of Multiagent System the optimum route had been determined. 2010 Elsevier Ltd. All rights reserved.