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A diffusion algorithm based on P systems for continuous global optimization
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AI
DOI：10.1016/j.jocs.2020.101112.png)
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Abstract
En 中文
This paper proposes a novel optimization algorithm, called Diffusion Algorithm Based on P Systems (DAPS), for continuous global optimization. This algorithm utilizes four different search strategies and a P system to explore the search space and find the global minima. These search strategies mimic the diffusion phenomena and a hybrid membrane structure inspired by chloroplasts and mitochondria is used as a distributed-parallel computing framework in the P system. The basic concepts and principles of the diffusion search strategies and the P system framework are explained in detail. For verifying the results of DAPS, comparisons with several well-known and recent metaheuristic optimization algorithms on 13 widely used benchmark functions are conducted. The experimental results demonstrate that DAPS is highly competitive and can provide better solution accuracy on the majority of the benchmark functions. (C) 2020 Elsevier B.V. All rights reserved.
Keywords:
Metaheuristic algorithm
Membrane
Computing
Diffusion mechanism
Continuous global optimization
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