A Hybrid Descent Method for Global Optimization |
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| Authors: | K.F.C. Yiu Y. Liu K.L. Teo |
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| Affiliation: | (1) Department of Applied Mathematics, Hong Kong Polytechnic University, Kowloon, Hong Kong;(2) Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong |
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| Abstract: | In this paper, a hybrid descent method, consisting of a simulated annealing algorithm and a gradient-based method, is proposed. The simulated annealing algorithm is used to locate descent points for previously converged local minima. The combined method has the descent property and the convergence is monotonic. To demonstrate the effectiveness of the proposed hybrid descent method, several multi-dimensional non-convex optimization problems are solved. Numerical examples show that global minimum can be sought via this hybrid descent method. |
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| Keywords: | Descent method Global minimum Simulating annealing |
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