Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
