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Willow Catkin Optimization Algorithm Applied in the TDOA-FDOA Joint Location Problem
Jeng-Shyang Pan1,2, Si-Qi Zhang1, Shu-Chuan Chu1
1College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
Abstract:
The heuristic optimization algorithm is a popular optimization method for solving optimization problems. A novel meta-heuristic algorithm was proposed in this paper, which is called the Willow Catkin Optimization (WCO) algorithm. It mainly consists of two processes: spreading seeds and aggregating seeds. In the first process, WCO tries to make the seeds explore the solution space to find the local optimal solutions. In the second process, it works to develop each optimal local solution and find the optimal global solution. In the experimental section, the performance of WCO is tested with 30 test functions from CEC 2017. WCO was applied in the Time Difference of Arrival and Frequency Difference of Arrival (TDOA-FDOA) co-localization problem of moving nodes in Wireless Sensor Networks (WSNs). Experimental results show the performance and applicability of the WCO algorithm.
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