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A comprehensive study of phase based optimization algorithm on global optimization problems and its applications
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DOI：10.1007/s10489-018-1306-z.png)
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Abstract
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Inspired by the completely different motional features of individuals in three different phases of nature, i.e. gas phase, liquid phase and solid phase, this paper presents a phase based evolutionary model. Based on the proposed model, a specific implementation termed Phase Based Optimization (PBO) was systematically given. Meanwhile, the search behavior analysis and the evolution process of population are provided to further understand the search mechanisms of PBO. To evaluate the performance of PBO, numerical experiments are carried out on twenty-three benchmark test functions consisting of different types of unimodal and multimodal functions. The obtained results demonstrate the better performance of PBO compared with eight state-of-the-art nature-inspired optimization algorithms. Besides, the effects of population size on PBO and the performance comparison of PBO under different problem dimensions are systematically investigated, respectively. Finally, PBO is applied to two application problems which are parameter estimation for frequency modulated sound waves synthesis and large scale transmission pricing problem, and the promising results indicate the applicability of PBO in both low and high dimensional real-world optimization problems.
Keywords:
Phase
Nature-inspired
Phase partitioning
Global optimization
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