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Parallel Compact Differential Evolution for Optimization Applied to Image Segmentation

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College of Computer Science and Engineering, Shandong University of Science and Technology, No. 579, QianWanGang Road, Qingdao 266590, China
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College of Science and Engineering, Flinders University, 1284 South Road, Clovelly Park, SA 5042, Australia
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School of Aeronautics and Astronautics, Yuquan Campus, Zhejiang University, No. 38, ZheDa Road, Hangzhou 310027, China
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Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(6), 2195; https://doi.org/10.3390/app10062195
Received: 17 February 2020 / Revised: 12 March 2020 / Accepted: 18 March 2020 / Published: 24 March 2020
(This article belongs to the Section Computing and Artificial Intelligence)
A parallel compact Differential Evolution (pcDE) algorithm is proposed in this paper. The population is separated into multiple groups and the individual is run by using the method of compact Differential Evolution. The communication is implemented after predefined iterations. Two communication strategies are proposed in this paper. The first one is to replace the local optimal solution by global optimal solution in all groups, which is called optimal elite strategy (oe); the second one is to replace the local optimal solution by mean value of the local optimal solution in all groups, which is called mean elite strategy (me). Considering that the pcDE algorithm does not need to store a large number of solutions, the algorithm can adapt to the environment with weak computing power. In order to prove the feasibility of pcDE, several groups of comparative experiments are carried out. Simulation results based on the 25 test functions demonstrate the efficacy of the proposed two communication strategies for the pcDE. Finally, the proposed pcDE is applied to image segmentation and experimental results also demonstrate the superior quality of the pcDE compared with some existing methods. View Full-Text
Keywords: parallel compact differential evolution (pcDE); compact differential evolution (cDE); image segmentation; communication strategies parallel compact differential evolution (pcDE); compact differential evolution (cDE); image segmentation; communication strategies
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Sui, X.; Chu, S.-C.; Pan, J.-S.; Luo, H. Parallel Compact Differential Evolution for Optimization Applied to Image Segmentation. Appl. Sci. 2020, 10, 2195.

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