Abstract
The problem of Multiple Observers Sitting on Terrain (MOST) is an important part in visibility-based terrain reasoning and many applications can be classified as this problem. Recent developments in this field concentrate on using heuristic algorithm, such as Simulated Annealing algorithm (SA), but it is still difficult because of unacceptable computing time and low solving precision. In this paper, a Cloud theory based Simulated Annealing algorithm (CSA) is introduced involving two innovations. The first is state changing by using X cloud generator which can make the position selection of observer controllable. The second is temperature annealing by using Y cloud generator which can produce approximatively continuous annealing temperature and fit the physical annealing process in nature much better. Theoretical analysis proves that CSA is convergent for MOST problem. Application experiments show that, using CSA for MOST problem, the average time cost decreases by 40%~60% and the average solution accuracy improves by 10% as compared with using SA.
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Lv, P., Yuan, L., Zhang, J. (2008). Cloud Theory Based Simulated Annealing Algorithm for Multiple Observers Sitting on Terrain Problem. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_90
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DOI: https://doi.org/10.1007/978-3-540-85984-0_90
Publisher Name: Springer, Berlin, Heidelberg
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