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A Novel Improved Bat Algorithm Based on Hybrid Parallel and Compact for Balancing an Energy Consumption Problem

1
Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou 350014, China
2
Department of Information Technology, University of Manage and Technology, Haiphong 180000, Vietnam
3
College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266510, China
4
College of Informatics, Chaoyang University of Science and Technology, Taichung 413, Taiwan
*
Authors to whom correspondence should be addressed.
Information 2019, 10(6), 194; https://doi.org/10.3390/info10060194
Received: 12 April 2019 / Revised: 11 May 2019 / Accepted: 27 May 2019 / Published: 3 June 2019
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Abstract

This paper proposes an improved Bat algorithm based on hybridizing a parallel and compact method (namely pcBA) for a class of saving variables in optimization problems. The parallel enhances diversity solutions for exploring in space search and sharing computation load. Nevertheless, the compact saves stored variables for computation in the optimization approaches. In the experimental section, the selected benchmark functions, and the energy balance problem in Wireless sensor networks (WSN) are used to evaluate the performance of the proposed method. Results compared with the other methods in the literature demonstrate that the proposed algorithm achieves a practical method of reducing the number of stored memory variables, and the running time consumption. View Full-Text
Keywords: improved bat algorithm; optimization deployment problems; probabilistic model; wireless sensor network improved bat algorithm; optimization deployment problems; probabilistic model; wireless sensor network
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Nguyen, T.-T.; Pan, J.-S.; Dao, T.-K. A Novel Improved Bat Algorithm Based on Hybrid Parallel and Compact for Balancing an Energy Consumption Problem. Information 2019, 10, 194.

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