Cloud theory-based simulated annealing algorithm and application

Authors:
Pin Lv;Lin Yuan;Jinfang Zhang
Affiliations:
National Key Laboratory of Integrated Information System Technology, South No. 4 Street, Zhong Guancun, Institute of Software, Chinese Academy of Sciences, Beijing 100190, PR China and Graduate Un ...;National Key Laboratory of Integrated Information System Technology, South No. 4 Street, Zhong Guancun, Institute of Software, Chinese Academy of Sciences, Beijing 100190, PR China and Graduate Un ...;National Key Laboratory of Integrated Information System Technology, South No. 4 Street, Zhong Guancun, Institute of Software, Chinese Academy of Sciences, Beijing 100190, PR China
Venue:
Engineering Applications of Artificial Intelligence
Year:
2009

Citing 2
Cited 5

Spatial Clustering Method Based on Cloud Model

FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02
Very fast simulated re-annealing

Mathematical and Computer Modelling: An International Journal

Cloud model-based control strategy on cluster communication coverage for wireless sensor networks

CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1
Cloud theory-based simulated annealing approach for scheduling in the two-stage assembly flowshop

Advances in Engineering Software
Incorporating utility and cloud theories for owner evaluation in tendering

Expert Systems with Applications: An International Journal
Simultaneous solving of balancing and sequencing problems with station-dependent assembly times for mixed-model assembly lines

Applied Soft Computing
Two-machine robotic cell scheduling problem with sequence-dependent setup times

Computers and Operations Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

Using the randomness and stable tendency of a Y condition normal cloud generator, a cloud theory-based simulated annealing algorithm (CSA) is originally proposed, whose characteristic is approximately continuous decrease in temperature and implied ''Backfire & Re-Annealing''. It fits the annealing process of solid matter in nature much better, overcomes the traditional simulated annealing algorithm (SA)'s disadvantages, which are slow searching speed and being trapped by local minimum easily, then enhances the veracity of final solution and reduces the time cost of the optimization process simultaneously. Theory analysis proves that CSA is convergent and typical function optimization experiments show that CSA is superior to SA in terms of convergence speed, searching ability and robustness. The result of the application using CSA for multiple observers sitting problem (MOST) in visibility-based terrain reasoning (VBTR) also declares the new algorithm's usefulness and effectiveness adequately.