Cloud Annealing: A Novel Simulated Annealing Algorithm Based on Cloud Model

Shanshan JIAO  Zhisong PAN  Yutian CHEN  Yunbo LI  

IEICE TRANSACTIONS on Information and Systems   Vol.E103-D   No.1   pp.85-92
Publication Date: 2020/01/01
Publicized: 2019/09/27
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2019EDP7059
Type of Manuscript: PAPER
Category: Fundamentals of Information Systems
simulated annealing,  Gaussian Cloud model,  cooling schedule,  solution perturbation,  optimization algorithm,  

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As one of the most popular intelligent optimization algorithms, Simulated Annealing (SA) faces two key problems, the generation of perturbation solutions and the control strategy of the outer loop (cooling schedule). In this paper, we introduce the Gaussian Cloud model to solve both problems and propose a novel cloud annealing algorithm. Its basic idea is to use the Gaussian Cloud model with decreasing numerical character He (Hyper-entropy) to generate new solutions in the inner loop, while He essentially indicates a heuristic control strategy to combine global random search of the outer loop and local tuning search of the inner loop. Experimental results in function optimization problems (i.e. single-peak, multi-peak and high dimensional functions) show that, compared with the simple SA algorithm, the proposed cloud annealing algorithm will lead to significant improvement on convergence and the average value of obtained solutions is usually closer to the optimal solution.